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1、Data Analytics Basics A Beginners GuideIntroductionAn overview of data analyticsThe applications of data analyticsReal-world use cases of data analyticsA glossary of data analytics termsBegin your journey in data analyticsWhere do I start?TABLE OF CONTENTS010203050710121|INTRODUCTIONAs the world mov

2、es further into the digital age,data analytics is increasingly becoming a key element in shaping a companys business strategy.Today,data influences every decision made by an organization,and this is driving the wide-scale adoption of data analytics,including machine learning technologies and artific

3、ial intelligence solutions.Realizing the powerful impact that data-driven insights can have on economic output,companies,across all sectors,are putting a great emphasis on boosting data analytics expertise and implementation.The heightened focus is propelling a surge in data analytics spending,refle

4、cted in various studies conducted by leading market research firms.A recent survey shows that the global market for data analytics will grow from USD 49 billion in 2019 to USD 77.64 billion in 2023,at a compound annual growth rate of 30.08 percent.Another study by Valuates Reports,cited by ,forecast

5、s that the market for data analytics will reach USD 512.04 billion by 2026,at a compound annual growth rate of 14.80%between 2019 and 2026.The data analytics market is booming,and with that,the demand for professionals with the right skills is soaring every day.A BHEF(Business-Higher Education Forum

6、)report shows that over 70%of CEOs in the United States prefer candidates with data analytics skills.With salaries ranging between USD 90,000 to USD 126,000,data analytics is not only the hottest IT job,but it is also one of the best-paying jobs in the world.If you are planning to pursue a career in

7、 data analytics,this is an ideal time to learn the skills that will prepare you for the future of business,where business analytics features prominently.This data analytics handbook acquaints you with this emerging field,providing an insight into the data analytics basics,its industry applications,r

8、eal-life use cases,key terminologies,the skills you must master,and the best course to take to land an exciting job in this field.2|AN OVERVIEW OF DATA ANALYTICSIn todays digital environment,a wide variety of sources-be it documents,electronic media,social platforms,organizations,or individuals-gene

9、rate massive amounts of unstructured or raw data.Systematically analyzing the data,and extracting actionable insights from it,is in recent times imperative for modern enterprises to strengthen their decision-making capabilities and maintain competitiveness.This is where data analytics comes in.Data

10、analytics involves multiple processes and applications that observe,transform,cleanse,and model data to derive meaningful information from large datasets.The professionals tasked with collecting,analyzing,cleansing,and profiling data are data analysts.They are also responsible for testing and develo

11、ping analytical models centered on the data obtained and analyzed.The basics of data analytics revolve around the collection,refining,and structuring of bulk data into a well-defined analytical model,using different programming languages such as Python,R,Scala,or SQL.Data analysts leverage the resul

12、ts gained from analytical models to identify groupings,trends,or relationships between various data types,which help organizations make informed decisions and meet business targets.3|THE APPLICATIONS OF DATA ANALYTICSThe major industries that are implementing advanced analytical technologies include

13、-RetailThe retail sector most likely sees the maximum application of cutting-edge data analytics techniques.With the industry steadily shifting to a digital ecosystem,an increasing number of retailers are using data analytics to understand consumer behavioral patterns,which helps the designing of cu

14、stomized services that enhance the buying experience.From engineering product recommendations to forecasting demand,and crisis control,global retail brands are deploying analytics for almost everything.HealthcareThe dramatic advent of innovative technologies is transforming the healthcare industry w

15、orldwide.Data analytics is playing a vital role in helping healthcare professionals find medical breakthroughs,deliver hyper-personalized treatment,and improve the patients quality of life.The medical industry relies on data analytics not to increase profits,but rather to improve the standard of hea

16、lthcare by proactively identifying diseases and reducing risk factors.Media and EntertainmentAn early adopter of data analytics technologies,the digital entertainment and media industry implements analytical tools and techniques for predicting viewer interests,personalizing content delivery,optimizi

17、ng media streams,targeting advertisements,and gaining useful insights from audience reviews.3|4|BankingAfter retail,the banking sector makes the most active use of data analytics.Analytical modeling allows banks to track down credit card misuse,detect fraudulent activities,and eliminate system looph

18、oles.Besides empowering banks to create personalized products,other data analytics applications in the financial sector include risk management,performance monitoring,and improved compliance reporting.TransportationOver the past few years,data analytics has been crucial for reforms in the transport

19、industry.Using a variety of historical trends,technical data,and real-time information,data analytics helps the transport industry effectively manage assets,predict traffic congestion,and focus on everyday occurrences while minimizing operating costs.4|5|REAL-WORLD USE CASES OF DATA ANALYTICSAs digi

20、tal technologies advance at a rapid pace,all organizations are getting fast access to a wealth of data.However,possessing enormous amounts of data makes no sense if businesses do not analyze the information to gain key insights.Heres how successful brands are using data analytics to address a divers

21、e range of business-critical needs.American multinational food,snack,and beverage corporation PepsiCo leverages data analytics to manage its supply chain efficiently.The company aims to ensure that its retail store shelves never run out of products.The organizations clients submit reports that conta

22、in Point of Sale(POS)and warehouse inventory data,which PepsiCo uses to forecast and reconcile the shipment and production needs.In this way,the firm ensures that its retailers get correct quantities of PepsiCo products on time.Amazon Fresh,a subsidiary of the global e-commerce company A,is an excel

23、lent instance of how data analytics can drive product development and innovation.Amazon implements data analytics to gain the expertise it needs to create and achieve greater value for its grocery delivery service brandAmazon Fresh.By putting an emphasis on data analytics,Amazon reviews how consumer

24、s buy their products and how the supplier interacts with them.The results procured from analytical reasoning help Amazon make changes wherever and whenever needed.6|Singapore-based multinational banking organization,United Overseas Bank,applies big data analytics to manage its risks.The financial in

25、stitution,in the recent past,conducted a test of its risk management system using big data analytics.UOB found that the new risk management system significantly reduced the time needed to calculate the total value of assets at risk.Previously,it took approximately 18 h,but after implementing data an

26、alytics,calculating risks is now a matter of few minutes.Netflix,Inc.,an American technology company and media services provider,is a brilliant example of how brands can use data analytics in targeted advertising.With well over 100 million subscribers,Netflix collects vast amounts of data,which they

27、 analyze to determine what a subscriber is more interested in.The worlds#1 internet entertainment service,Netflix,achieves this through data analytics,which provides them with smart insights based on a subscribers past search data.Intercontinental beverage corporation,Coca-Cola,deploys data analytic

28、s for driving customer retention.The 130-year-old company,in 2015,launched a data-driven customer loyalty program to bolster its digital strategy.While consumers made the most of the rewards,Coca-Cola collected crucial personal information for data analytics,which helped the organization improve cus

29、tomer interactions.Data analytics not only empowered the super-brand to keep its customers,but it also enabled the company to upsell its new products while boosting the consumption of existing product lines.6|7|A GLOSSARY OF DATA ANALYTICS TERMSTo become a part of the data analytics industry,it is i

30、mportant to be familiar with the key terminologies related to the field.Here is a list of terms and jargons that surround data analytics.Data ScienceAn interdisciplinary application,data science uses various processes,scientific methods,and algorithms to derive insights and knowledge from an array o

31、f structured and unstructured data.Researchers link this field to big data analytics,data mining,and machine learning.Data MiningData mining refers to the methods and techniques used for identifying patterns within big datasets.It leverages database systems,statistics,and machine learning to detect

32、trends and patterns.HadoopThe Hadoop framework incorporates a set of open-source software tools that allow distributed computing across several computer clusters.It enables data professionals to solve various problems involving large datasets.Apache Hadoop facilitates scaling up from a single server

33、 to hundreds of machines,where each machine offers local storage and computation.8|Predictive ModellingPredictive modeling uses statistical analysis for predicting outcomes using data models.The models can predict whatever organizations want,from corporate earnings to technological advances,televisi

34、on ratings,or sports results.MapReduceSoftware for distributed processing of datasets,MapReduce algorithms for data analytics comprises a map method for filtering,and a reduce procedure for summary operation.NoSQL DatabaseNoSQL databases provide storage and retrieving mechanisms for data,modeled in

35、a way different from tabular relations seen in relational database applications.These databases have been around since the 1960s,but at the start of the 21st century,Web 2.0 companies coined the name“NoSQL”.PythonA high-level,interpreted,general-purpose computer language developed by Guido van Rossu

36、m,Python incorporates a design philosophy that focuses on readable-code with significant use of whitespace.RA free-to-use software environment,data professionals use the R programming language for computational statistics.Data miners,data analysts,and statisticians use R for data analysis and statis

37、tical software development.9|Recommendation EngineA recommendation engine,also called a recommendation system,recommends products,services,and content to end consumers,based on data analytics.The recommendations rely on several factors,including customer behavioral patterns,or user search history.Sp

38、arkApache Spark is a general-purpose,open-source,cluster-computing software framework.The widely-adopted computer program,which integrates modules for SQL,graph processing,machine learning,and streaming,offers a solid programming interface for cluster computers with inherent fault tolerance and data

39、 parallelism.Structured DataStructured data refers to“clean”data,organized as tables or charts containing columns,rows,or multidimensional arrays.The easy-to-understand,readily available structured data,expedites analytical,and data mining processes.Unstructured DataUnstructured data is unorganized,

40、raw information,not arranged or structured in a defined format,such as tables or charts.Raw data is heavy,incomplete,inconsistent,or inaccurate,until analysts cleanse and refine the unstructured information to draw meaningful insights.VisualizationVisualization is the visual representation of datase

41、ts in the form of lists,graphs,charts,or maps.The display of data in a graphical or pictorial format makes recognizing patterns and gaining insights easier.10|BEGIN YOUR JOURNEY IN DATA ANALYTICSIn this section,well talk about how you can launch your career in data analysis.The Skills Youll NeedA ca

42、reer in the field of data analytics requires you to master the following skills:ProgrammingAn aspirant must have a comprehensive knowledge of programming languages,including R,Python,and SQL.Other useful languages include Java,Oracle,SAS,MATLAB,Tensorflow,Scala,and Julia.MathThose in data analyst ro

43、les must be strong in basic math skills,specifically statistics.Thats because they are faced with many day-to-day situations when these skills comes in handy,for example,when dealing with small datasets,which are best tackled with the statistical capabilities of Microsoft Excel.11|Data Processing Pl

44、atformsData analysts need to be familiar with big data processing platforms like Hadoop and Apache Spark in order to handle large datasets.The working knowledge and understanding of these frameworks allow data analysts to query data across multiple devices,and scrub,model,and interpret it to gain mo

45、re in-depth insight into data patterns and identify relationships and trends.VisualizationAlong with extracting insights out of datasets,it is equally important to be able to present them clearly,particularly for stakeholders.For this reason,a data analyst must know how to produce graphical represen

46、tations of the findings using visualization tools,such as Tableau.Machine LearningBeing at the heart of any large-scale data analysis,automation is a crucial part of this field.This requires a data analyst to have considerable machine learning skills to be able to create,apply,and train the most fit

47、ting models and algorithms to datasets to find solutions for specific problems.Besides,a data analyst must also possess:Skills to interpret,analyze,and model data Problem-solving skills Interpersonal skills Communication skills12|WHERE DO I START?You should start by making the most of online resourc

48、es and books that are available for free.There are some exciting stuff on the Internet that can help you build a solid foundation.These days,employers are not emphasizing on formal education to fill talent gaps,however,having an academic degree in computer science,mathematics,or statistics will help

49、 you climb up the career ladder quickly.The easiest way to establish yourself as a data analyst is to get certified by a top-rated institution,such as Simplilearn,which is one of the worlds leading certification providers.This data analytics handbook suggests Simplilearn because of the wide variety

50、of courses it offers.From Data Analytics Course for Beginners to Data Analyst Masters program in collaboration with IBM,and Post Graduate Program in Data Analytics,Simplilearn positions itself uniquely to cater to the needs of every aspiring data analyst.Begin Now!12|USA Simplilearn Americas,Inc.201 Spear Street,Suite 1100,San Francisco,CA 94105United StatesPhone No:+1-844-532- INDIA Simplilearn Solutions Pvt Ltd.#53/1 C,Manoj Arcade,24th Main,Harlkunte2nd Sector,HSR LayoutBangalore-560102Call us at:1800-212-7688