Data Analytics full course

Hey everyone welcome to this data analyst full course video by simply learn in this full course you will learn all about how to become a data analyst this video will help you get acquainted with the duties and career prospects of a data analyst along with various data analytics concepts here we will start by understanding the career of a data analyst and what are data analysts duties are then we will list the top 10 data analyst skills and the top 10 data analysis tools moving on we will distinguish a data analyst from a data scientist and we will also pick the role of a data analyst against a few other roles like business analyst and data engineer we will then move on to learning data analytics with python following which we will learn a few excel concepts that can help you in your role as a data analyst we will also look into pandas and matplotlib next we will understand data analytics using r not to forget we are also going to learn about sql finally we will conclude this full course by understanding the top data analyst interview questions that you could be asked in your next interview our team of experts will take you through the various topics in this full course you can learn all of these topics in under 12 hours but before we begin make sure to subscribe to our youtube channel and hit the bell icon to never miss an update from simply learn in a world where there is data generation every millisecond the role of a data analyst holds paramount importance this video will help you understand what a data analyst does and the various skills required to back this position before understanding the job role of a data analyst let's understand the meaning of the term data analytics so what does the term analyze mean it merely means to scrutinize something to derive meaningful conclusions from it well data analytics also works similarly it is the process by which useful insights are extracted from raw data by studying and examining it carefully these insights can be related to business information market trends product innovations and profit loss report to name a few an interesting comparison i'm sure all of you have played with jigsaw puzzles at some point in time for that first you would have to gather all the pieces together and then fit them accordingly to bring out a beautiful picture isn't it we can simply relate the process of data analytics to how you make a jigsaw puzzle as you can see here data refers to the raw data which can be structured semi-structured or unstructured in nature the process of data analytics incorporates collecting data from various sources cleaning it and then finally transforming it into something meaningful which can be interpreted by humans this information can be visually presented in the form of graphs and charts which provide precise results of the analysis various technologies tools and frameworks are used in the analysis process organizations take the help of data analytics to convert the available raw data into meaningful insights hence there is a high requirement for professionals who can play with data and help organizations with crucial decision making there are many job roles in the field of data analytics if you have watched our previous video on data analytics courier you would have seen a few of these roles out of all the job roles an important role is that of a data analyst an interesting thing about this job role is that it can be taken up by freshers as well it can embark on your career in the field of data analytics it is a lucrative career as the field of data analytics is only going to continue to blossom in the years to come so let's see who exactly a data analyst is a data analyst is a person who collects processes and performs analysis on large data sets here the statistical analysis is done on various data sets every business generates and collects data be it marketing research sales figures customer feedback logistics or transportation costs a data analyst will take all of this data and figure out various measures such as how to price new materials how to reduce transportation costs how to provide better customer experience or how to deal with issues that cost the company money data analysts also deal with data handling data modeling and data reporting a data analyst has a number of duties to perform let's have a look at their responsibilities now first and foremost a data analyst is required to recognize and understand the organization's goal this helps in streamlining and planning the analysis process accordingly data analysts assist the available resources understand the business problem and gather the right data this step is done by collaborating with different team members such as programmers business analysts and data scientists data analysts need to use queries to gather information from a database they write complex sql queries and scripts to gather and extract information from several databases and data warehouses they are responsible for data mining as well here data is mined from various sources and then organized in order to obtain a new information from it this is a vital role of a data analyst as they have to extract data from various sources in order to work on it with this data they can build models that can reduce the complexity and increase the efficiency of the whole system another crucial step in data analysis is data cleaning and data wrangling usually the data you can collect is often messy and has a lot of missing values so it's important to clean this data to make it ready for analysis data analysts use a number of statistical and analytical tools including programming languages for performing analysis and logical examination of data using different libraries and packages data analysts discover trends and patterns from complex data sets this will help them find more unseen insights from the data to make business predictions another important role of a data analyst is to prepare summary reports for the leadership team so that they can make timely decisions for this data analysts use multiple data visualization tools some of these tools are discussed as part of skills required which we will see later finally data and lists interact with the development team business and management team as well as with data scientists to ensure proper implementation of business requirements and to figure out opportunities for better process improvement now let us look at the various skills required to become a data analyst so the first skill is more of a prerequisite you should hold a degree in any relevant field be it engineering computer science information technology electrical or mechanical engineering you can also be a graduate in statistics or economics also you should have domain knowledge in the field you are currently working in or the role you're applying for the next important skill is that you should have good hands-on experience with programming languages such as r python and javascript this would help you write programs to solve complex problems then you should have a good experience working with databases and data analysis tools such as writing sql queries and procedures knowledge of microsoft excel ibm spss and matlab to analyze trends forecast data and plan to drive accurate insights you must have a strong understanding of statistics and machine learning algorithms these include concepts such as hypothesis testing probability distributions regression analysis and various classification and clustering techniques and finally a data analyst should be able to create different reports with the help of charts and graphs using several data visualization tools such as tableau and power bi they must have good presentation skills as well this will help them convey their ideas to clients and stakeholders better now that we have looked at the various skills required to become a data analyst let's now see the average annual salary that a data analyst earns here we can have a look at the salary ranges of both in u.

S and in india so a data analyst in the united states can earn a minimum salary of 43 dollars to a maximum of eighty five thousand dollars per year in india you can earn anywhere between one lakh ninety eight thousand rupees to nine lakh twenty four thousand rupees per annum the data analyst role is in very high demand with companies looking for professionals who can handle their data effectively and efficiently so let's look at the different companies hiring for the data analyst role as you see here we have the american e-commerce giant amazon the american multinational technology company microsoft capital one which is one of the largest banking companies in the us then we have the popular retail company walmart then we have paypal next we have the internet and search engine giant google social media firms facebook and twitter as well as apple and bloomberg with that let me now tell you how simply learn can help you learn data analytics and guide you to become a data analyst so in a new tab i'll search for simplylearn.com then here on the search bar i look for data analyst let me now click on the first link which is data and list i'll open this in another tab as you can see on your screens this is the data and list masters program and it is in collaboration with ibm on the right hand side you can see the different courses that will be covered as a part of the program you will learn introduction to data analytics business analytics with excel then you have tableau followed by power bi later on in the course you will learn programming basics and data analytics with python then r programming and finally you will get to work on a capstone project this is a kind of certificate you would receive after completing the course it will have your name along with ibm and simply learn logo these are some of the tools that will be covered in this program you will learn excel then numpy panda scipy ibm watson power bi tableau python and r the course advisor for this program is ronald van glun below you can see the entire course curriculum and the different courses that you will learn in this program also there are a few electives that you can choose in this course there's data science in real life programming refresher industry master class data analytics and there is sql training as well let's quickly understand how important a career in data analytics is and what the future holds for professionals in this domain let's take a look at the growth of data so back in the early 2000s there was relatively less data generated but with a rapid rise in technologies and with the increase in the number of various social media platforms and multinational companies across the globe the generation of data has increased by leaps and bounds did you know that according to the idc the total volume of data is expected to reach 175 zettabytes in 2025 now that's a lot of data let's take a look at how organizations leverage all of this data as you know there are zillions of companies across the world these companies generate loads of data on a daily basis when i say data here it simply refers to business information customer data customer feedback product innovations sales reports and profit loss reports to name a few companies utilize all of this data in a wise way they use all of this information to make crucial decisions that can either hamper or boost their businesses you might have heard of the term data is the new oil well it definitely is but only if organizations analyze all the available data very well then this oil is definitely valuable and for that we have data analytics organizations take the help of data analytics to convert the available raw data into meaningful insights so what is data analytics technically you can say it is a process wherein data is collected from various sources then cleaned which involves removing irrelevant information and then finally transformed into some meaningful information that can be interpreted by humans various technologies tools and frameworks are used in the analysis process as you might have heard of the term data never sleeps well it surely doesn't every millisecond some of the other data is generated and this is a constant process this process is only going to increase in the near future with the advent of newer technologies the data analytics domain holds paramount importance in every sector companies want to leverage on all the generated big data and boost their businesses they need professionals who can play with data and convert them into crucial insights organizations are constantly on the lookout for such candidates and this opportunity will only increase as data is only going to grow every second so if you want to start your career in this field or if you want to switch your job role into a role in the data analytics domain then we have a set of job profiles that you can look at we will look into six job roles in the data analytics field and learn what each job role is all about the responsibilities of a professional working in that particular role the skills required to get that particular job the average annual salary of a professional working in that role and finally the company is hiring for that role so let's start off first we have the job role of a data analyst a data analyst is a person who collects processes and performs statistical analysis of large data sets every business generates and collects data be it marketing research sales figures logistics or transportation costs a data analyst will take this data and figure out a variety of measures such as how to price new materials how to reduce transportation costs or how to deal with issues that cost the company money they deal with data handling data modeling and reporting now talking about their responsibilities data and lists recognize and understand the organization's goal they collaborate with different team members such as programmers business analysts engineers and data scientists to identify opportunities for solving business problems data analysts write complex sql queries scripts and store procedures to gather and extract information from multiple databases they filter and clean data using different modern tools and techniques and make it ready for analysis they also perform data mining from primary and secondary data sources data analysts identify analyze and interpret trends in complex data sets this is done using statistical tools such as r and sas another key responsibility of a data analyst is to create summary reports and build various data visualizations for decision making and presenting it to the stakeholders next let us discuss the important skills that you need to know to become a data analyst firstly you should have a bachelor's degree in computer science or information technology a master's degree in computer applications or statistics is also preferable you must have a good understanding of programming languages like r python javascript and also understand sql in addition to that it is beneficial if you have hands-on experience with statistical and data analytics tools such as sas minor microsoft excel and ssas basic understanding of machine learning and its algorithms would be an advantage acquaint yourself with descriptive predictive prescriptive and inferential statistics most importantly you need to have a good working knowledge of various data visualization software along with presentation skills this will help you pitch in your ideas and view points to the clients and stakeholders better now talking about their salaries a data analyst earns nearly 5 lakhs 23 000 rupees per annum in india while in the united states they earn around 62 453 dollars per annum let's now look at a few of the companies hiring data analysts so as you can see we have the american e-commerce joint amazon then we have microsoft the american online payment company paypal then we have walmart bloomberg and capital one so that was all about data analyst the next job role is of a business analyst business analysts help guide businesses in improving products services and software through data-driven solutions they are responsible for bridging the gap between it and business using data analytics to evaluate processes determine requirements and deliver data-driven recommendations and reports to executives and stakeholders business analysts are responsible for creating new models that support business decisions and come up with initiatives and strategies to optimize costs now let us look at the various responsibilities of a business analyst business analysts have a good understanding of the requirements for business their vital role is to work in accordance with relevant project stakeholders to understand their requirements and translate them into details which the developers can understand they frequently interact with developers and come up with a plan to design the layout of a software application they also run meetings with stakeholders and other authorities they engage with business leaders and users to understand how data driven changes to products services software and hardware can improve efficiencies and add value they ensure that the project is running smoothly as per the requirements and the design planned through user acceptance and validation testing they make sure all the features are being incorporated into the application findings where each requirement of the client is mentioned in detail now let us look at the skills required for a ba a bachelor's degree in the field of science engineering or statistics or any related domain will suffice knowledge of programming languages such as python and java is beneficial you should be really good at writing complex sql queries and you should also have knowledge of various business process models along with knowledge of programming languages ideas about statistical analysis and predictive modelling is necessary decision making strong analytical and problem solving skills are necessary to solve software and business issues you also need to have excellent presentation and communication skills both oral and written moving on to their salary a business analyst is expected to earn around seven lakh rupees per annum in india in the us they earn nearly 68 346 dollars per annum iqea dell philips honeywell the famous american messaging platform whatsapp the uk-based company ernest and young are few of the companies hiring for business analysts up next we have the job role of a database administrator a database administrator is a specialized computer systems administrator who maintains a successful database environment by directing or performing all related activities to keep the organization's data secure they are responsible for storing organizing and retrieving data from several databases and data warehouses their top responsibility is to maintain data integrity this means that database administrator will ensure that the data is secure from unauthorized access moving on to their responsibilities a database administrator develops designs and maintains a database to ensure that the data in it is properly stored organized and managed well they maintain data integrity by avoiding unauthorized access and they keep databases up to date they run tests and modify the existing databases to ensure that they operate reliably they also inform end users of changes in databases and train them to utilize systems they need to cooperate with programmers data analysts and the it staffs to ensure smooth running and maintenance of databases database administrators are responsible for taking system backups in case of power outages and other disasters so they should have an efficient disaster recovery plan now let's have a look at their skills to become a database administrator you should have a bachelor's degree in computer science or information technology knowledge of programming languages such as python java and scala is important you need to carry at least three to five years of experience in data management you need to have an understanding of different databases such as oracle db mongodb mysql server and postgresql also they should have an idea about database design and writing sql queries finally you need to have a good understanding of operating systems such as windows mac os and linux along with storage technologies talking about their salary a database administrator in india can earn up to four lakh 97 000 rupees per annum in the us they earn around 78 000 per annum let's have a look at the companies hiring for database administrators so as you see here we have bookmyshow oracle the american mnc intel amazon robert half and the new york times to name a few fourth in the list of job roles we have data engineer a data engineer someone who's involved in preparing data for analytical and operational uses a data engineer transforms data into useful format for analysis they build and test scalable big data ecosystems for businesses a data engineer is an intermediary between a data analyst and a data scientist now let's jump into their responsibilities data engineers develop test and maintain architectures they are responsible for managing optimizing and monitoring data retrieval storage and distribution throughout the organization they discover opportunities for data acquisition find trends in data sets and develop algorithms to help make raw data more useful to the enterprise data engineers build large data warehouses using etl for storing and retrieving data they also recommend ways to improve data quality and efficiency along with building algorithms to help give easier access to raw data data engineers often work with big data and submit their reports to data scientists for analysis purpose they need to recommend and sometimes implement ways to improve data reliability efficiency and quality moving on to the skills of a data engineer a data engineer should hold a bachelor's degree in computer science or information technology they should have good hands-on experience with python r and java also data engineers should be well versed with big data technologies such as hadoop apache spark scala cassandra and mongodb data warehousing and detail experience are essential to this position along with in-depth knowledge of sql and other database solutions basic knowledge of statistical analysis will be an advantage along with idea about operating systems here is what a data engineer can earn so in india a data engineer can earn up to eight lakhs eighty-five thousand rupees per annum while they can earn around hundred and three thousand dollars a year in the usa we have cab gemini shorter stock the american provider of stock photography spotify accenture genpak and facebook hiring data engineers the next exciting job role is of a data scientist a data scientist is a professional who uses statistical methods data analysis techniques machine learning and related concepts in order to understand and analyze data to draw business conclusions they make sense to messy and unstructured data and bring value out of it they employ techniques and theories drawn from many fields within the context of mathematics statistics computer science and information science a data scientist understands the challenges in business and comes up with the best solutions using modern tools and techniques to analyze visualize and build prediction models to make business decisions let us now look at their responsibilities in the industries data scientists clean process and manipulate data using several data analytics tools they perform ad hoc data mining collect large sets of structured and unstructured data from disparate sources they design and evaluate advanced statistical models to work on big data they also create automated anomaly detection systems and keep constant track of their performance data scientists interpret the analysis of big data to discover solutions and opportunities a data scientist takes input from data analysts and engineers to formulate the results they use visualization packages and tools to create reports and dashboards for relevant stakeholders they also adopt new business models and approaches apart from this they regularly build predictive models and machine learning algorithms now moving on to the skills of a data scientist a bachelor's degree in computer science or information technology will be fine but a master's degree in the field of data science will hold a major advantage you also need to have a good experience in the analytics domain you should be proficient in programming languages such as python java and c plus knowledge of perl will also be an advantage familiarity with apache hive big and apache spark is necessary along with the knowledge of hadoop in addition to knowing programming languages you also need to know sql machine learning and deep learning data visualization and bs skills are necessary for creating reports and dashboards you should also be able to communicate and present information and ideas properly now talking about their salary a data scientist in india can expect an annual salary of 10 lakhs 47 000 rupees per year meanwhile in the us they can earn up to 113 000 dollars per annum that's a lot of money from the many companies hiring for data scientists here we have a few companies named they are yet again amazon citibank apple google the japanese electronic commerce and online retailing company rakuten and facebook and finally we have machine learning engineer machine learning engineers are professionals who develop intelligent machines that can learn from vast amounts of data and apply knowledge without human intervention they use different algorithms and statistical modeling to make sense of data they design and develop machine learning and deep learning algorithms their main goal is to create self-running software let's have a look at the responsibilities of a machine learning engineer machine learning engineers research design and develop machine learning systems they use exceptional mathematical skills in order to perform faster computations and work with algorithms to create sophisticated models they perform a b testing and use data modeling to fine-tune the results they use data modeling and evaluation strategy to find hidden patterns and predict unseen instances machine learning engineers work closely with data engineers to build data pipelines and interact with stakeholders to get a clarity on the requirements most importantly they analyze complex data sets to verify data quality perform model tests and experiments choose to implement the right machine learning algorithm and select the right training data sets moving on to their skills a machine learning engineer should have a degree in computer science and information technology they should have an advanced degree in computer science or maths in addition to this they should also have experience in the same domain they should be proficient in programming languages such as python rc plus plus and java knowledge of statistics probability and linear algebra is necessary as all the machine learning algorithms have been derived from mathematics also having an idea of signal processing would be beneficial machine learning engineers need to have a good understanding of data manipulation and machine learning libraries such as numpy panda scikit-learn etc they should have good oral and written communication skills let us now have a look at their salary structure a machine learning engineer earns 8 lakh rupees per annum in india while in the us they can earn around 114 000 a year now that's a whopping amount isn't it let's have a look at the companies hiring machine learning engineers so as you see we have amazon microsoft oracle salesforce rapido and accenture to name a few that was all about the job role of a machine learning engineer now that we have seen the different job roles in the field of data analytics let's also go ahead and see how an ideal resume of a data analyst should look like seen on your screens is a sample resume of a data analyst you can grab some ideas from this and incorporate them in your resume nowadays it's quite common to have a professional photograph of yours on the resume you can go ahead and have that then your name in bold followed by your contact details like email id and phone number then moving on you would have to write a summary briefly explain your current job role and what you're looking for in the future having a linkedin profile link works well these days employers can just go ahead and look at your profile and gauge you well make sure to have an active linkedin profile in addition to linkedin profile it's also good to have a github profile link which can show your coding or other technical skills if it's impressive enough then a lot of times the rest of your resume is just secondary as i mentioned this is a resume of a data analyst so as you can see in the summary here we have just spoken about the basic responsibilities of a data analyst moving on to the experience part you have to write the job title and below that you can mention the company and the tenure accordingly here you would have to give a brief description of achievements in the organization any relevant accomplishments related to the job you're applying for the tools and the various technologies you have worked with so in this sample you can see we have spoken about data visualization using r and tableau next we have spoken about how the candidate has worked with other teams for a better business outcome most of the data and lists use sql and excel to handle data for reporting and database maintenance and we have mentioned that here as well do make sure that you always specify the tools you use then you can also mention if you have worked on improving data delivery for example here we have spoken about developing and optimizing sql queries data aggregations and etl to improve data delivery finally you can speak a bit about your reporting skills and if needed elaborate on it usually professionals would have worked in a similar domain before becoming a data analyst here we have taken the role of a statistical assistant as the first job since it's easier for a candidate with this job role to shift into the data analytics field nevertheless y'all can still mention your prior experience here be it in any domain under the responsibilities for this job role we have given basics such as coding data prior to computer entry compiling statistics from various reports computing and analyzing data and finally some visualization and reporting moving to the education here you can mention the name of your degree and the university name if you have a post graduation well and good you can list both the degrees here also if you have any certifications you can mention them here under the education category now moving to the skills depending on your skills and your choice you can either shift this part to the beginning of the resume or have it here as you see on your screens this is just a different way of displaying your skill sets you can have all the five stars colored if you are excellent in that particular tool or language as you see it's crystal clear as to what the candidate's strong areas are you can have various categories like shown for example under software development you can list the languages that you know and how proficient you are in those particular languages it's clear that the candidate knows python better than javascript here so the employer gets a clear idea about the skills you possess and the depth of it similarly you can mention the databases as well the few mentioned here are more or less a requirement to become a data analyst at least sql is a must not to forget data visualization is also very important when it comes to the job role of a data analyst mention the tools you know here and similarly give yourself a rating out of five five stars shaded being the highest here we have mentioned tableau and excel which are more than sufficient to become a data analyst moving to the non-technical skills you can mention the languages you know here here we have taken english and german in addition to the languages you can also feel free to mention the extracurricular activities that you are good at so this is how an ideal resume of a data analyst should look like you can alter it according to your achievements skills and experience welcome to this session on top 10 skills to become a data analyst before diving into our topic let's quickly speak about the job role of a data analyst in this 21st century data analytics is used in every sector be it in organizations where meaningful insights are drawn pertaining to the growth of the company or be it in fighting the ongoing pandemic covid19 data finds its importance everywhere speaking of the role of a data analyst he or she is a skilled professional who is responsible for collecting and processing data they perform analysis on large data sets they also deal with data handling data modeling and reporting a data analyst understands the trends and insights that are revealed in massive data sets so if you want to become a data analyst then there are a few skills that you need to possess let's have a look at the top 10 skills that can help you back the position of a data analyst here we will look into both technical and non-technical skills at number 10 we have mathematics data and lists work with a lot of structured and unstructured data in order to analyze and understand all the acquired data a strong foundation in mathematics is essential of the data analysis will use linear algebra statistics probability and calculus for performing analysis and for the logical examination of data hypothesis testing such as the null hypothesis and alternate hypothesis analysis is another crucial task that data analysts perform to ensure that the data they have collected is relevant for analysis they need to perform z test t-test and chi-square test to make sure the sample data is good for analysis also data analysts build machine learning models for solving business problems using classification regression and clustering algorithms so to understand the working of these algorithms knowledge of mathematics is compulsory moving to number nine we have the big data tools and frameworks data and lists deal with complex and inaccurate data that is really huge in volume now to handle this data they need to possess big data technology skills such as hadoop and the tools that are part of its ecosystem hadoop provides the hadoop distribution file system to store data in several chunks scoop is popularly used as a data ingestion tool for extracting data from htfs onto relational databases data analysts use hedgebase which is a column-oriented database for processing semi-structured data there are other frameworks such as apache big and high for processing and analyzing data using big latin scripts and hive query language it would be an advantage for a data analyst to have an idea about these tools and frameworks at number eight we have data cleaning and data wrangling in this modern era of internet and social media data is being generated every second and often this data is noisy and messy containing missing values data is also often unstructured and this could be a problem for data analysts to perform analysis on such data so they need to pre-process the data and clean it using various tools and techniques to make it fit for analysis data analysts must transform the data into the right format for carrying out analytics they should also have data manipulation and data mining skills to find out unseen trends and patterns from the data some of the tools they should have knowledge of are open refine and tri-factor wrangler they need to have hands-on experience in certain numerical computation and data manipulation libraries such as numpy pandas dplyr scipy and idr at number seven we have bi tools for data visualization in order to understand the complexities of business and derive the desired solution data analysts should have an idea about business intelligence tools business intelligence is a process to analyze and visualize vast volumes of data it helps in creating reports and dashboards to better understand the trends in data bi tools help data analysts to sort and filter the data perform data manipulation by joining multiple data sets and build different charts and graphs to present the data in a pictorial format it also helps them to forecast the data to make future predictions the reports and dashboards created using bi tools can help data and lists convey their ideas to clients and stakeholders some of the popular bi tools used in analytics are power bi tableau click view and sas bi all these tools feature in the gartner magic quadrant for 2020 for business intelligence and analytics at number six we have microsoft excel and etl tools every data analyst should possess a good working knowledge of microsoft excel excel is the most preferred tool for analytics that is commonly used by managers across the globe microsoft excel has really good features to manipulate and analyze structured data that is in the form of rows and columns it provides a lot of inbuilt numerical and text functions you also have the advantage of creating pivot tables and pivot charts along with creating different charts and graphs for building a report you can explore advanced features such as excel macros good knowledge of data warehousing and etl tools is important data analysts often gather data from several data sources then they manipulate and transform data using different techniques and finally they load the data to a data warehouse for easy access some of the popular etl and data warehousing tools are informatica and talent at number five we have programming languages data analysts should have excellent hands-on programming knowledge for solving complex business problems they need to know programming languages such as python r sas and java python and r are the most widely used languages in the field of data analytics and machine learning both python and r are open source programming languages they are easy to learn and implement python has built-in mathematical functions regular expressions and libraries like pandas numpy matplotlib and c-bond for data analysis r supports packages such as supplier d-player tie-dr tidy words gg plot and lattice for manipulating and visualizing the data sas is another preferred programming software for statistical analysis and model building while java is mainly suitable for writing user-defined methods and object-oriented programming at number four we have the most important skill for any data analyst which is database and sql the database is a storage container where companies store huge volumes of data organizations deal with vast volumes of structured and semi-structured data on a daily basis this data is stored in relational and non-relational databases in order to retrieve process and manipulate the data from such databases data analysts should use rdbms and nosql databases such as microsoft sql server mysql ibm db2 mongodb and postgresql they should know how to write sql queries using commands such as select insert update delete drop and truncate data analysts must have advanced querying skills like implementing where and having clauses to filter the data using built-in sql functions joining tables and writing store procedures to automate complex tasks those were all the technical skills that are required to be possessed by a data analyst now that you had a look at all the technical skills you must note that the role of a date analyst is a blend of both technical and non-technical you need to focus on certain non-technical skills as well to become a full-fledged data analyst so let's now move on and look at what non-technical skills are required to become a data analyst if you enjoy watching informative tech videos like this one consider subscribing to simply learn's channel to stay up to date on the trending technologies and hit the bell icon to never miss an update in the future at number three we have problem solving data analysts should be prepared to face several barriers on a daily basis being able to problem-solve the way out of obstructions is an essential skill there can be multiple issues like budget constraints short deadlines and so on these problems would require you to come up with innovative solutions hence no matter what the circumstances having strong problem solving skills will always be a virtue being a data analyst also requires you to think like an analyst analytical skills also known as logical thinking refers to breaking down problems logically having strong analytical skills will help you arrive at a buy solution in any situation based on information and facts complex problems can be solved this way critical thinking also goes hand in hand with analytical skills critical thinking is a self-guided and self-disciplined way of thinking which attempts to reason in a fair-minded way as a data analyst critical thinking will help you stay grounded when you are searching for a solution to a tricky problem you should also be capable of making well thought independent decisions there are a number of tips that can help you improve your critical thinking skills moving on to number two we have business knowledge business knowledge or domain knowledge refers to holding a sound understanding of the domain you are working in this knowledge is different for different organizations for example if you're working in the automobile industry you might need to understand how systems work and how its output can be potentially influenced irrespective of where you work you need to have good business knowledge and understand what you're analyzing you should be in a position to understand the various business problems and how to solve them only if you have a strong industry knowledge can you try to improve the business if you keep yourself updated with market trends you can understand where your company stands and accordingly build a business model this will also help you assist your business in exploring greener pastures so now let's have a look at what's at number one here we have communication and presentation this might seem like a very common skill but it's not as easy as it sounds data analysts interact with various teams to ensure proper implementation of business requirements and for this collaboration to run smoothly communication is very important the ability to communicate in numerous ways is a key data analyst skill this includes writing speaking presenting and listening written communication is crucial you will be required to write up your analysis and provide regular documentations of it data visualization and presentation skills go hand in hand presenting your analysis results to various team members and stakeholders holds paramount importance you might also need to be in a state to explain a complex topic to non-technical teammates there is no point of a great analysis if you are unable to explain it through your presentation you can master the presentation skill with regular practice until you are comfortable to explain in front of a bunch of people having said that you should also be very crisp with your presentations you need to be clear direct and focus on the result rather than deviating from your topic like they say you need to hit the bullseye before i start off with the top 10 data analysis tools i'd like to talk a bit about data analysis so have you ever wondered why data analysis is important there are zillions of companies across the world all these companies generate a lot of data they literally work with this generated data these companies depend on data to make crucial decisions which can impact their businesses data in its raw format has to be converted into meaningful information which can then be used by organizations this is done by analyzing the generated data and for this we have data analysis so what is data analysis data analysis is not just a single step but a set of processes it is the process of collecting data then cleaning it when i say cleaning it simply means removing the irrelevant data and then this data is transformed into meaningful information we can simply relate this process to how you make a jigsaw puzzle just like how you gather all the pieces together and fit them accordingly to bring out a beautiful picture data analysis also works on almost the same grounds to achieve the goals of data analysis we use a number of data analysis tools companies rely on these tools to gather and transform their data into meaningful insights so which tool should you choose to analyze your data which tool should you learn if you want to make a career in this field we will answer that in this session after extensive research we have come up with these top 10 data analysis tools here we will look at the features of each of these tools and the companies using them so let's start off at number 10 we have microsoft excel all of us would have used microsoft excel at some point right it is easy to use and one of the best tools for data analysis developed by microsoft excel is basically a spreadsheet program using excel you can create grids of numbers text and formulae it is one of the widely used tools be it in a small or large setup the interface of microsoft excel looks like this let's now move on to the features of excel firstly excel works with almost every other piece of software and office we can easily add excel spreadsheets to word documents and powerpoint presentations to create more visually appealing reports or presentations the windows version of excel supports programming through microsoft's visual basic for applications vba programming with vba allows spreadsheet manipulation that is difficult with standard spreadsheet techniques in addition to this the user can automate tasks such as formatting or data organization in vba one of the biggest benefits of excel is its ability to organize large amounts of data into orderly logical spreadsheets and charts by doing so it's a lot easier to analyze data especially while creating graphs and other visual data representations the visualization can be generated from specified group of cells those were few of the features of microsoft excel let's now have a look at the companies using it most of the organizations today use excel few of them that use it for analysis are the uk based company ernest and young then we have urban pro wipro and amazon moving on to our next data analysis tool at number nine we have rapidminer a data science software platform rapidminer provides an integrated environment for data preparation analysis machine learning and deep learning it is used in almost every business and commercial sector rapidminer also supports all the steps of the machine learning process seen on your screens is the interface of rapidminer moving on to the features of rapidminer firstly it offers the ability to drag and drop it is very convenient to just drag drop some columns as you are exploring a data set and working on some analysis rapidminer allows the usage of any data and it also gives an opportunity to create models which are used as a basis for decision making and formulation of strategies it has data exploration features such as graphs descriptive statistics and visualization which allows users to get valuable insights it also has more than 1500 operators for every data transformation and analysis task let's now have a look at the companies using rapidminer we have the caribbean airline leeward islands air transport next we have the united health group the american online payment company paypal and the austrian telecom company mobilecon so that was all about rapidminer now let's see which tool we have at number eight we have talent at number eight talent is an open source software platform which offers data integration and management it specializes in big data integration talent is available both in open source and premium versions it is one of the best tools for cloud computing and big data integration the interface of talent is as seen on your screens moving on to the features of talent firstly automation is one of the great boons talent offers it even maintains the tasks for the users this helps with quick deployment and development it also offers open source tools talon lets you download these tools for free the development costs reduce significantly as the processes gradually speed up talent provides a unified platform it allows you to integrate with many databases sas and other technologies with the help of the data integration platform you can build flat files relational databases and cloud apps 10 times faster those were the features of talon the companies using talent are air france l'oreal cab gemini and the american multinational pisa restaurant chain dominos next on the list at 7 we have 9 constance information minor on nime is a free and open source data analytics reporting and integration platform it can integrate various components for machine learning and data mining through its modular data pipelining concept nime has been used in pharmaceutical research and other areas like crm customer data analysis business intelligence text mining and financial data analysis here is how the interface of nime application looks like now coming to the 9 features 9 provides an interactive graphical user interface to create visual workflows using the drag and drop feature use of jdbc allows assembly of nodes blending different data sources including pre-processing such as etl that is extraction transformation loading for modeling data analysis and visualization with minimal programming it supports multi-threaded in-memory data processing 9 allows users to visually create data flows selectively execute some or all analysis steps and later inspect the results models and interactive views nimeserver automates workflow execution and supports team-based collaboration nime integrates various other open source projects such as machine learning algorithms from becca hedge tour keras park and our project 9 allows analysis of 300 million custom addresses 20 million cell images and 10 million molecular structures some of the companies hiring for nime are united health group asml fractal analytics atos and lego group let's now move on to the next tool we have sas at number six sas facilitates analysis reporting and predictive modeling with the help of powerful visualizations and dashboards in sas data is extracted and categorized which helps in identifying and analyzing data patterns as you can see on your screens this is how the interface looks like moving on to the features of sas using sas better analysis of data is achieved by using automatic code generation ads as sql sas allows you to access through microsoft office by letting you create reports using it and by distributing them through it sas helps with an easy understanding of complex data and allows you to create interactive dashboards and reports let's now have a look at the companies using sas we have companies like gen pact iqea accenture and ibm to name a few that was all about sas so for all those who joined in late let me just quickly repeat our list at number 10 we have microsoft excel then at number nine we have rapidminer at number eight we have talent at number seven we have nine and at number six we have sas so far do you all agree with this list let us know in the comment section below let's now move on to the next five tools in our list so at number 5 we have both r and python yes we have two of them in the fifth position r is a programming language which is used for analysis as well it has traditionally been used in academics and research python is a high level programming language which has a python data analysis library it is used for everything starting from importing data from excel spreadsheets to processing them for analysis this is the interface of r next up is the interface of the python jupyter notebook let's now move on to the features of both r and python when it comes to the availability of r and python it is very easy both r and python are completely free hence it can be used without any license r used to compute everything in memory and hence the computations were limited but now it has changed both are in python have options for parallel computations and good data handling capabilities as mentioned earlier as both r and python are open in nature all the latest features are available without any delay moving on to the companies using r we have uber google facebook to name a few python is used by many companies again to name a few we have amazon google and the american photo and video sharing social networking service instagram that was all about rn python at number 4 we have apache spark apache spark is an open source engine developed specifically for handling large-scale data processing and analytics spark offers the ability to access data in a variety of sources including hadoop distributed file system htfs openstack swift amazon s3 and cassandra it allows you to store and process data in real time across various clusters of computers using simple programming constructs apache spark is designed to accelerate analytics on hadoop while providing a complete suite of complementary tools that include a fully featured machine learning library a graph processing engine and stream processing so this is how the interface of apache spark looks like now let's look at the important features of apache spark spark stores data in the ram hence it can access the data quickly and accelerate the speed of analytics spark helps to run an application in a hadoop cluster up to 100 times faster in memory and 10 times faster when running on disk it supports multiple languages and allows the developers to write applications in java scala r or python spark comes up with 80 high level operators for interactive querying sparkcore for batch processing joins stream against historical data or run ad hoc queries on stream state analytics can be performed better as spark has a rich set of sql queries machine learning algorithms complex analytics etc apache spark provides fault tolerance through spark rdd spark resilient distributed data sets are designed to handle the failure of any worker node in the cluster thus it ensures that the loss of data reduces to zero conviva netflix iqea lockheed martin and ebay are some of the companies that use apache spark on a daily basis at number 3 we have another important growing data analysis tool that is click view qlikview software is a product of click for business intelligence and data visualization qlikview is a business discovery platform that provides self-service bi for all business users and organizations with qlikview you can analyze data and use your data discoveries to support decision making clickview is a leading business intelligence and analytics platform in gartner magic quadrant on the screen you can see how the interface of qlikview looks like now talking about its features clickview provides interactive guided analytics with in-memory storage technology during the process of data discovery and interpretation of collected data the qlikview software helps the user by suggesting possible interpretations clickview uses a new patent in memory architecture for data storage all the data from the different sources is loaded in the ram of the system and it is ready to be retrieved from there it has the capability of efficient social and mobile data discovery social data discovery offers to share individual data insights within groups or out of it a user can add annotations as an addition to someone else's insights on a particular data report qlikview supports mobile data discovery within an html5 enabled touch feature which lets the user search the data and conduct data discovery interactively and explore other server based applications qlikview performs olap and etl features to perform analytical operations extract data from multiple sources transform it for usage and load it to a data warehouse the companies that can help you start your career in qlikview are mercedes-benz cab gemini citibank cognizant and accenture to name a few at number two we have power bi power bi is a business analytic solution that lets you visualize your data and share insights across your organization or embed them in your app a website it can connect to hundreds of data sources and bring your data to life with live dashboards and reports power bi is the collective name for a combination of cloud-based apps and services that help organizations collate manage and analyze data from a variety of sources through a user-friendly interface power bi is built on the foundation of microsoft excel and has several components such as windows desktop application called power bi desktop and online software as a service called power bi service mobile power bi apps available on windows phones and tablets as well as for ios and android devices here is how the power bi interface looks like as you can see there is a visually interactive sales report with different charts and graphs moving on to the features of power bi it has an easy drag and drop functionality with features that make data visually appealing you can create reports without having the knowledge of any programming language power bi helps users see not only what's happened in the past and what's happening in the present but also what might happen in the future it offers a wide range of detailed and attractive visualizations to create reports and dashboards you can select several charts and graphs from the visualization pane power bi has machine learning capabilities with which it can spot patterns in data and use those patterns to make informed predictions and run what-if scenarios power bi supports multiple data sources such as excel tech csv oracle sql server pdf and xml files the platform integrates with other popular business management tools like sharepoint office 365 and dynamics 365 as well as other non-microsoft products like spark hadoop google analytics sap sales force and mailchimp some of the companies using power bi are adobe axa carlsberg capgemini and nestle moving on to the next tool so any guesses as to what we have at number one you can comment in the chat section below finally on the top of the pyramid we have tableau gartner's magic quadrant of 2020 classified tableau as a leader in business intelligence and data analysis tableau interactive data visualization software company was founded in jam 2003 in mountain view california tableau is a data visualization software that is used for data science and business intelligence it can create a wide range of different visualization to interactively present the data and showcase insights the important products of tableau are tableau desktop tableau public tableau server tableau online and tableau reader this is how the interface of tableau desktop looks like now coming to the features of tableau data analysis is very fast with tableau and the visualizations created are in the form of dashboards and worksheets tableau delivers interactive dashboards that support insights on the fly it can translate queries to visualizations and import all ranges and sizes of data writing simple sql queries can help join multiple datasets and then build reports out of it you can create transparent filters parameters and highlighters tableau allows you to ask questions spot trends and identify opportunities with the help of tableau online you can connect with cloud databases amazon redshift and google bigquery the companies using tableau are deloitte adobe cisco linkedin and the american e-commerce giant amazon to name a few and there you go those are the top 10 data analysis tools let's now have a question and answer session please feel free to post your queries in the comments section and we'll respond in the chat before the question answer session let's recap quickly in the meanwhile y'all can post your questions in the comment section below so at number 10 we have microsoft excel then at number nine we have rapidminer at number eight we have talent at number seven we have nine at number six we have sas r and python at number five apache spark at number four click view at number three power bi at number two and finally we have tableau topping the list at number one currently all of us are living in an information driven world and organizations rely on data for various decision makings this in turn provides a lot of job opportunities for candidates who can play with data out of the many job roles in the field of data science the two popular ones are that of a data scientist and a data analyst haven't we all wondered at some point as to what the exact difference is between these two job roles oh wait are they the same well they define various ways and you will see how in this video we will start off by looking at the job descriptions of both the data scientist and the data analyst then we will look at their responsibilities and skill set we will also have a look at their salary structure and the various companies hiring for these professionals so without further ado let's get started let's have a look at the job description now a data scientist is a professional who uses different statistical methods data analysis techniques and machine learning in order to understand and analyze data in order to arrive at business conclusions they proactively fetch information from a plethora of sources and analyze it for better understanding about how the business performs and they also build ai tools that automate certain processes within the company they derive meaning out of messy and unstructured data a data scientist is usually a senior most member in the team moving to the description of data analyst a data analyst is responsible to collect process and perform analysis on large data sets they deal with data handling data modeling and reporting they are sometimes the entry level members into the data analytics team they bring technical expertise to ensure the quality and accuracy of the data then process design and present it in ways to help people businesses and organizations make better decisions after a few years of experience data analysts can move into the roles of a data engineer and a data scientist now that we have understood the job descriptions let's go ahead and understand the various roles and responsibilities of a data scientist and a data analyst firstly data scientists are responsible for performing cleaning processing and manipulation of data using several data analytics tools they also perform ad hoc data mining and collect large sets of structured and unstructured data from a number of sources secondly data scientists interpret the data using various statistical methods they design and evaluate advanced statistical models to work on big data thirdly data scientists regularly build predictive models and machine learning algorithms to work on vast volumes of data lastly data scientists use visualization packages and tools to create reports and dashboards for relevant stakeholders they also work with data analysts and data engineers to formulate the analysis results let's now have a look at the various responsibilities of a data analyst the first responsibility of a date analyst is to recognize and understand the company's goal this in turn helps in streamlining the whole analysis process they are required to assess the available resources comprehend the business problem and gather the right set of data this step is done by collaborating with different team members such as data scientists business analysts and programmers they gather data from various databases and warehouses through querying they write complex sql queries and scripts to gather and extract information data analysts also filter and clean data to get the required information they are responsible for data mining as well data is mined from various sources and then organized in order to obtain new information from it data analysts identify and analyze trends in complex data sets using various statistical tools a data analyst is also responsible for creating summary reports for the leadership team so that they can make timely decisions data analysts use multiple data visualization tools for achieving this in order to achieve all the above mentioned responsibilities data scientists and data analysts are required to possess a rich skill set let's now have a look at few of the most important skills required to back the position of a data scientist the basic requirement to become a data scientist is that you must have a bachelor's degree in computer science or information technology but a master's degree in the field of data science will be a lot more beneficial you also need to have a good experience in the analytics domain as i mentioned before this role is a senior role and to get here the right amount of experience is a must let's have a look at the tools you need to know knowledge of microsoft excel is good it is one of the most basic requirements speaking of programming languages you should be good at python c plus plus and java knowledge of perl is a brawny po