Business Data Analytics Part 1 PDF

Business Data Analytics Igor Arkhipov, CBAP Part 1. Introduction to business data analytics Introduction to business data analytics  Data is a collection of unorganized facts or observations that can be processed to obtain valuable information — Guide to Business Data...

Business Data Analytics Igor Arkhipov, CBAP Part 1. Introduction to business data analytics Introduction to business data analytics  Data is a collection of unorganized facts or observations that can be processed to obtain valuable information — Guide to Business Data Analytics, IIBA In general, there are two types of data. Qualitative data is descriptive information. Quantitative data is numerical information (this means it can be presented as numbers). It describes something; it can be observed and recorded but is non-numerical in nature. Quantitative data can be: Data that represents different types of Discrete (it can take only certain numbers, categories such as gender, types of products of a e.g. amount of people in the room) company, and different departments is Continuous (it can take any value within a categorical data. given range, e.g. average height of all the people in the room). If there is an order to the categorical data then it is referred to as ordinal data, such as grades in a subject (for example, A, B, C). Analytics is the science of examining raw data and information in order to draw insights. — Guide to Business Data Analytics, IIBA The volume of data is enormous Year 2020: The amount of data in the world was estimated to be 44 zettabytes (World Economic Forum)  At the beginning of 2020, the number of bytes in the digital universe was 40 times bigger than the number of stars in the observable universe. (World Economic Forum)  Business data analytics is a specific set of techniques, competencies, and practices applied to perform continuous exploration, investigation, and visualization of business data. — Guide to Business Data Analytics, IIBA Why do the organisations invest into data analytics? 1/ To support more informed business decision-making 2/ To deliver on their strategic imperatives 3/ To innovate 4/ To obtain competitive advantage in the marketplace Data analysis ❖ It disrupts existing markets while enabling new products and impacts how services and creating new markets businesses ❖ ❖ It drives increased efficiency It identifies growth opportunities make and drives innovation ❖ It improves risk management decisions What is the difference between business data analytics (BDA) and data science? Business data analytics is an area of study that Data science is a term that is loosely defined in targets effective business decision-making as the industry. Typically it evolves around opposed to using the rigorous technical combining computer science, modeling, statistics, know-hows through which data is analyzed. analytics, and math skills to solve business problems. In this course, we will separate the two disciplines assuming they work together during some of the BDA tasks. In real life, a trained single individual can play both roles simultaneously. Use of business data analytics for business decision-making is accomplished in the following ways: Asking foundational Highlighting how Managing data quality questions to shape enterprise data is strategic imperatives organized and managed Understanding and Integrating insights into communicating initiatives: analytics results Enterprise business processes Tech People What is business data analytics  Business data analytics is a specific set of techniques, competencies, and practices applied to perform continuous exploration, investigation, and visualization of business data. The desired outcome of a business data analytics initiative is to obtain insights that can lead to improved decision-making. — Guide to Business Data Analytics, IIBA Business data analytics can be defined more specifically through several perspectives: 1/ Movement 2/ Capability 3/ Data centric activity set 4/ Decision making paradigm 5/ Set of practices and technologies  Evidence through data becomes the BDA as a driver of business decisions and change. movement This is especially apparent in the industries like insurance, web It is management philosophy that personalisation, and medical includes evidence-based services. approach to identifying and solving problems  Business data analytic competencies extend beyond those required to complete analytical activities, they BDA as a include capabilities such as innovation, culture creation, and capability process design. Executive decision is not enough to It includes the competencies introduce analytics capability to the possessed by both the business. You need skilled organisation and its employees. individuals, reliable data sources, and infrastructure.  BDA in addition to those introduces BDA as a the following: Data-Centric ❖ ❖ planning strategy analysis Activity Set ❖ stakeholder collaboration and management ❖ solution designing Data analytics consist of six core ❖ recording and verifying activities: analytics approaches ❖ accessing ❖ analyzing ❖ tracking and managing analytics ❖ examining ❖ interpreting recommendations ❖ aggregating ❖ presenting results  BDA as a Evidence from data is an enabler for Decision Making informed decision making that is Paradigm more persuasive than just following instincts. It makes making business data Releasing new functionality through analytics a mechanism for A/B testing is a good example of it. informed decision-making across the organization.  BDA defines six domains: BDA as a as a Set 1. Identify the Research Questions of Practices and 2. 3. Source Data Analyze Data Technologies 4. Interpret and Report Results 5. Use Results to Influence It is a framework to execute Business Decision-Making analytics initiatives. 6. Guide Organizational-Level Strategy for Business Data Analytics. The BDA cycle  The scientific method is an empirical method of acquiring knowledge Induction Hypothesis Scepticism Observation Experiment Report Analyze data Deduction conclusions Induction vs Deduction Inductive reasoning moves from specific Deductive reasoning works from the more observations to broader generalizations and general to the more specific. Sometimes this is theories. Informally, we sometimes call this a informally called a “top-down” approach. “bottom up” approach. Theory Tentative Hypothesis hypothesis Pattern Observation Observation Confirmation If happens then will happen? Is different to ? Does affect ? The scientific process starts by asking a question that scopes the research. The BDA cycle Pose a Create a Test the Do research question hypothesis hypothesis Communicate Troubleshoot Analyse data / Is the test results / Use as problems/ Draw effectively knowledge for consider another conclusions capturing data? future research method Despite being ❖ The business data analytics process may differ depending on based on the ❖ the type of analysis taking place Testing may not always include an scientific experiment to collect data ❖ It is necessary to perform extra method, BDA data validation and verification prior to analysis differs a bit The BDA objectives Predicting the price and quality of...is more wine based reliable than on weather expert conditions... opinion The objective of business data analytics is to explore and investigate business problems or opportunities through a course of scientific inquiry. There are four types of analytics methods: 1/ Descriptive 2/ Diagnostic 3/ Predictive 4/ Prescriptive  Offline Online Descriptive 39 4 Provides insight into the past by 29 27 describing or summarizing data. 4 5 Answers the question: “What has 20 35 happened?” 5 25 22 15 Q1 Q2 Q3 Q4 Sales figures, FY 2018  Diagnostic Explores why an outcome occurred. Answers the question: “Why did a certain event occur?” Factors contributing to drop in sales in Q1  Predictive Analyzes past trends in data to provide future insights. Answers the question: “What is likely to happen?” Projected growth in demand  Baseline Campaign effect Prescriptive 5 Uses the findings from different 26 forms of analytics to quantify the 23 anticipated effects and outcomes 7 of decisions under consideration. 20 6 17 4 Answers the question: “What 2 should happen if we do …?” 15 16 17 19 Week 1 Week 2 Week 3 Week 4 Projected effect of a marketing campaign on sales Past Descriptive Diagnostic What happened? Why did it happen?? Present / Predictive Future What is likely to happen? Future Prescriptive What should we do? Business data analytics and business analysis  Business analysis is the practice of enabling change in an enterprise by defining needs and recommending solutions that deliver value to stakeholders. — A Guide to the Business Analysis Body of Knowledge® (BABOK® Guide), IIBA Business ❖ BA can increase effectiveness of the analytics initiatives by analysis ❖ providing the business context BA defines the focus for the analytics problem and sets the scope ❖ BA aids in the collection of data ❖ BA communicates the results and facilitates the implementation of business decisions made as a result of analysis  ❖ Analytics focus primarily on data analysis in a systematic process Data analytics ❖ Typical practices and procedures in data analytics are used to sort, process, and analyze the data once assembled ❖ Once the data analysis is complete, business analysis activities are performed to interpret the results obtained from data analytics and transform information into business Technique: understanding probability Probability is simply how likely something is to happen 70% 3 6  odd odd 1 odd odd even even odd even even odd 4 Technique: probability tree 100% 30% 100% 100% 100% 100% 100% 100%  First contact 70% 30% 70% 30% Second contact 70% 30% 49% 21% Third contact 70% 30% 34.3% 14.7% 65.7%  100% 100% 65.7% 100% 100% 100% 100% 100% 100% 100%  First contact 70% 30% 70% 30% Second contact 70% 30% 49% 21% 51% 51% 100% 51% 100% 51% 100%  First contact 70% 30% 70% 30% Second contact 70% 30% 49% 21% Third contact 70% 30% 34.3% 14.7%  Is contact sick? 49% 51% 49% 51% Contact 70% 30% 35.7% 15.3% 84.7%  First contact 84.7% 15.3% 84.7% 15.3% Second contact 84.7% 15.3% 71.74% 12.96% Third contact 84.7% 15.3% 60.76% 10.98% 39.24%  51% 100% 39.24% 51% 100% 51% 100% Case study: Taking context into account 50% HIV test 99.99% 99.99% chances you’ve got HIV 50% 99.99% x10 000 x 9 999 x1 x 9 998 x1 x1  The example here is an implementation of Bayes' law that describes the probability of an event based on prior knowledge of conditions that might be related to the event.