Word of the Day: business analytics (BA)

Word of the Day Daily updates on the latest technology terms | July 10, 2019 business analytics (BA) Business analytics (BA) is the iterative, methodical exploration of an organization's data, with an emphasis on statistical analysis. Business analytics is used by companies that are committed to making data-driven decisions. Data-driven companies treat their data as a corporate asset and actively look for ways to turn it into a competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business, and an organizational commitment to using data to gain insights that inform business decisions. Specific types of business analytics include: Descriptive analytics, which tracks key performance indicators to understand the present state of a business; Predictive analytics, which analyzes trend data to assess the likelihood of future outcomes; and Prescriptive analytics, which uses past performance to generate recommendations about how to handle similar situations in the future.   How business analytics works   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.   Initial 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. Business analytics vs. business intelligence   While the terms business intelligence and business analytics are often used interchangeably, there are some key differences:   BI vs BA Business Intelligence Business Analytics   Answers the questions: What happened? When? Who? How many? Why did it happen? Will it happen again? What will happen if we change x? What else does the data tell us that never thought to ask?   Includes: Reporting (KPIs, metrics) Automated Monitoring/Alerting (thresholds) Dashboards Scorecards OLAP (Cubes, Slice & Dice, Drilling) Ad hoc query Statistical/Quantitative Analysis Data Mining Predictive Modeling Multivariate Testing     Business analytics vs. data science The more advanced areas of business analytics can start to resemble data science, but there is also a distinction between these two terms. Even when advanced statistical algorithms are applied to data sets, it doesn't necessarily mean data science is involved. That's because true data science involves more custom coding and exploring answers to open-ended questions. Data scientists generally don't set out to solve a specific question, as most business analysts do. Rather, they will explore data using advanced statistical methods and allow the features in the data to guide their analysis. There are a host of business analytics tools that can perform these kinds of functions automatically, requiring few of the special skills involved in data science. Business analytics applications Business analytics tools come in several different varieties: Data visualization tools Business intelligence reporting software Self-service analytics platforms Statistical analysis tools Big data platforms Self-service has become a major trend among business analytics tools. Users now demand software that is easy to use and doesn't require specialized training. This has led to the rise of simple-to-use tools from companies such as Tableau and Qlik, among others. These tools can be installed on a single computer for small applications or in server environments for enterprise-wide deployments. Once they are up and running, business analysts and others with less specialized training can use them to generate reports, charts and web portals that track specific metrics in data sets. Quote of the Day "Companies often report the highest analytics success when blending teams, so data scientists working alongside business analysts can produce operational benefits." - Ed Burns Trending Terms business intelligence statistical analysis predictive analytics descriptive analytics prescriptive analytics data scientist data artist Learning Center Guide to telling stories with data: How to share analytics insights Using data visualizations to convey information can be a challenge. Learn more about telling stories with data in this guide to effective data storytelling. Data scientist vs. business analyst: What's the difference? Many people confuse data scientists with business analysts, but the roles are distinct. One career expert explains data scientist vs. business analyst roles, how they are similar and where they differ. The direction of business intelligence is changing to forward As business intelligence is changing quickly, one of the key trends will be the ability for BI platforms to look forward and be predictive, rather than just detail what has already taken place. Building leaner, meaner BI data sources Now that business intelligence has broken free from traditional data warehousing, the data that feeds it has taken center stage. In this tip, get advice for building better BI data sources and getting the most out of BI analysis and reporting. Make better business decisions with financial analytics Your organization can take advantage of financial analytics to predict the future, make better business decisions and automate data reporting. Not only that, but by using predictive and advanced analytics tools, you can improve the overall performance of your finance department. Quiz Yourself The use of a spreadsheet when a data warehouse was required created a situation _______ effective analysis was impossible. a. where b. in which Answer Stay in Touch For feedback about any of our definitions or to suggest a new definition, please contact me at: mrouse@techtarget.com Visit the Word of the Day Archives and catch up on what you've missed! FOLLOW US About This E-Newsletter This e-newsletter is published by the TechTarget network. To unsubscribe from Whatis.com, click here. Please note, this will not affect any other subscriptions you have signed up for. TechTarget, Whatis, 275 Grove Street, Newton, MA 02466. Contact: webmaster@techtarget.com Copyright 2018 TechTarget. All rights reserved.