Business intelligence and analytics


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Business intelligence and analytics

  1. 1. Business intelligence Business intelligence refers to competencies, technologies, process ,application and practices used to support evidence based decision making process of organization .It is collection of approaches for gathering ,storing ,analyzing and providing access to data that helps to gain better insight and take decision on fact based evidence. What is BI used for? Organizations’ use Business Intelligence to gain data-driven insights on anything related to business performance. It is used to understand and improve performance and to cut costs and identify new business opportunities, this can include, among many other things: Analyzing customer behaviors, buying patterns and sales trends. Measuring, tracking and predicting sales and financial performance Budgeting and financial planning and forecasting Tracking the performance of marketing campaigns Optimizing processes and operational performance Improving delivery and supply chain effectiveness Web and e-commerce analytics Customer relationship management Risk analysis Strategic value driver analysis Basics of busines intelligence : 1. Gathering data
  2. 2. Gathering data is concerned with collecting or accessing data which can be used for decision making process .It is used for collection of performance measurement. Example like transactional systems that keep logs of past transactions, point-of-sale systems, web site software, production systems that measure and track quality, etc. 2. Storing data Storing data is concerned with making sure that data is filed and stored in proper way so that it can be easily found and used for analysis purpose .Data warehouse is used to store the data under different category . 3. Analyzing data Analyzing data is important step to gain better insight that will support organization decision making process .It is done with help of statistical tools, data mining approaches or visual analytics. 4. Providing access In order to support decision making the decision makers need to have access to the data. Access is needed to perform analysis or to view the results of the analysis. The former is provided by the latest software tools that allow end-users to perform data analysis while the latter is provided through reporting, dashboard and scorecard applications. What Is Data Mining? Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis. Data mining uses sophisticated mathematical algorithms to segment the data and evaluate the probability of future events. Data mining is also known as Knowledge Discovery in Data (KDD). The key properties of data mining are:  Automatic discovery of patterns  Prediction of likely outcomes  Creation of actionable information  Focus on large data sets and databases Business Intelligence is more than Software Tools and Technology The term Business Intelligence is often used in a very narrow way to refer to software applications used to analyze an organization’s raw data. Terms often associated with BI in an IT sense are data mining, online analytical processing, querying and reporting. Business analytics Business analytics (BA) is the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis. Business analytics is used by companies committed to data-driven decision making.
  3. 3. BA is used to gain insights that inform business decisions and can be used to automate and optimize business processes. Data-driven companies treat their data as a corporate asset and leverage it for competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business and an organizational commitment to data-driven decision making. Examples of BA uses include: • Exploring data to find new patterns and relationships (data mining) • Explaining why a certain result occurred (statistical analysis, quantitative analysis) • Experimenting to test previous decisions (A/B testing, multivariate testing) • Forecasting future results (predictive modeling, predictive analytics) Once the business goal of the analysis is determined, an analysis methodology is selected and data is acquired to support the analysis. Data acquisition often involves extraction from one or more business systems, cleansing, and integration into a single repository such as a data warehouse or data mart. The analysis is typically performed against a smaller sample set of data. Analytic tools range from spreadsheets with statistical functions to complex data mining and predictive modeling applications. As patterns and relationships in the data are uncovered, new questions are asked and the analytic process iterates until the business goal is met. Deployment of predictive models involves scoring data records (typically in a database) and using the scores to optimize real-time decisions within applications and business processes. BA also supports tactical decision making in response to unforeseen events, and in many cases the decision making is automated to support real-time responses. While the terms business intelligence and business analytics are often used interchangeably, there are some key differences: BI vs. BA Business Analytics What happened? Answers the questions: Business Intelligence Why did it happen? When? Will it happen again? Who? What will happen if we changex? How many? What else does the data tell us that never thought to ask? Reporting (KPIs, metrics) Statistical/Quantitative Analysis Automated Monitoring/Alerting
  4. 4. Includes: (thresholds) Data Mining Dashboards Predictive Modeling Scorecards Multivariate Testing OLAP (Cubes, Slice & Dice, Drilling) Ad hoc query Business intelligence provides a way trough data gathering through asking question, online analytical process and reporting, while business analytics uses more quantitative and statistical data for decision making and predictive modeling. Business intelligence team task: 1. Working with business staff to understand the kind of information they need to know / decisions they need to make; 2. Identifying data that would be needed to produce this information and from which systems the data would come from; 3. Understand the data and how it would be fed into the data warehouse (what does the data mean? what are the data quality issues? etc.); 4. Setup ETL processes to get this data into the data warehouse; 5. Develop reports that join / filter / aggregate / the data and show results in a nice clear report format or dashboard. 6. Maintain these feeds and ensure end users are clear on what reports are showing. Competitive intelligence: Competitive intelligence is process of ethically and legally gathering, analyzing information about competitor’s strength and weakness to enhance business decision making. It grouped into two categories – 1. Tactical – Short term and seeks to provide input into issues such as capturing market share and increase revenue of company.
  5. 5. 2. StrategicStrategic competitive intelligence focuses on long term issues such as risk and opportunities facing the enterprise. Information analyzed to the point where strategic decision can be made. It is tool to alert management to early treats and opportunities in the market. It requires for reasonable assessment of data and gives best views and approximation of market and the competition. Competitive intelligence is understanding and learning of what is happening outside your business in the world so that you can be competitive in the market. For example to sales representative .intelligence means tactical advice on how to best bid for lucrative contract. To top management, it represents insight to gain market share against competitors.