What is Business Analytics? Use data to improve business results

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What is Business Analytics?

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Research firm Gartner defines business analytics as “solutions used to build analysis models and simulations to create scenarios, understand realities, and predict future states.”

While quantitative analysis, operational analysis, and data visualizations are key components of business analytics, the goal is to use the insights gained to shape business decisions. Discipline is a key facet of the business analyst role.

The Wake Forest University School of Business notes that key business analytics activities include:

  • Identify new patterns and relationships with data mining
  • Using quantitative and statistical analysis to design business models
  • A/B and multivariate testing based on results
  • Forecasting future business needs, performance and industry trends through predictive modeling
  • Communicate results to colleagues, management and clients
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What are the benefits of business analysis?

Business analytics can help you improve operational efficiency, better understand your customers, predict future results, glean insights to aid decision-making, measure performance, drive growth, uncover hidden trends, generate leads and move your business in the right direction, according to digital skills training company Simplilearn.

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What is the difference between business analytics and data analytics?

Business analytics is a subset of data analytics. Data analytics is used in all disciplines to find trends and solve problems using data mining, data cleaning, data transformation, data modeling, etc. Business analytics also involves data mining, statistical analysis, predictive modeling, etc., but focuses on making better business decisions.

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What is the difference between business analysis and business intelligence?

Business analytics and business intelligence (BI) have similar goals and are often used as interchangeable terms, but BI can be considered a subset of business analytics. BI focuses on descriptive analysis, data collection, data warehousing, knowledge management, and data analysis to evaluate past business data and better understand currently known information. While BI studies historical data to guide business decision-making, business analytics is all about looking to the future. It uses data mining, data modeling and machine learning to answer “why” something happened and predict what might happen in the future.

Business Analysis Techniques

According to Harvard Business School Online, there are three main types of business analysis:

  1. Descriptive analysis: What’s going on in your business right now? Descriptive analytics uses historical and current data to describe the current state of the organization by identifying trends and patterns. This is the domain of BI.
  2. Predictive analytics: What will probably happen in the future? Predictive analytics is the use of techniques such as statistical modeling, forecasting, and machine learning to make predictions about future outcomes.
  3. Prescriptive analysis: What do we have to do? Prescriptive analytics is the application of testing and other techniques to recommend specific solutions that will deliver desired business results.

Simplilearn adds a fourth technique:

  1. Diagnostic analysis: Why does this happen? Diagnostic analysis uses analytical techniques to uncover the factors or reasons for past or current performance.

Business Analysis Examples

San Jose Sharks boost fan engagement

Beginning in 2019, the San Jose Sharks began integrating their operational data, marketing systems and ticket sales with front-end fan experiences and promotions to enable the NHL hockey team to capture and to quantify the needs and preferences of its fan segments: subscribers, occasional visitors and newcomers. It uses the information to power targeted marketing campaigns based on actual shopping behavior and experience data. When implementing the system, Neda Tabatabaie, vice president of business analysis and technology for the San Jose Sharks, said she expected a 12% increase in ticket revenue, an expected reduction 20% increase in subscriber churn and a 7% campaign increase. effectiveness (measured in number of clicks).

GSK finds opportunities to reduce inventory

As part of a program designed to accelerate its use of enterprise data and analytics, pharmaceutical titan GlaxoSmithKline (GSK) has designed a set of analytics tools focused on inventory reduction opportunities in the supply chain. business supply. The suite of tools included a digital value stream map, safety stock optimizer, inventory lane report, and planning cockpit.

Shankar Jegasothy, director of supply chain analytics at GSK, says the tools have helped GSK gain better visibility into its end-to-end supply chain and then use predictive and prescriptive analytics to guide inventory and planning decisions.

Kaiser Permanente streamlines its operations

Kaiser Permanente Healthcare Consortium uses analytics to reduce patient wait times and the time hospital managers spend manually preparing data for operational activities.

In 2018, the consortium’s IT function launched Operations Watch List (OWL), a mobile app that provides a comprehensive, near real-time view of key hospital quality, safety and throughput metrics hospitals, demand and availability of beds, and number of discharged patients).

In its first year, OWL reduced patient wait times for emergency department admission by an average of 27 minutes per patient. Surveys have also shown that hospital managers have reduced the time spent manually preparing data for operational activities by an average of 323 minutes per month.

Business analytics professionals must master a variety of tools and programming languages. According to the Harvard Business Analytics program, the best tools for business analytics professionals are:

  • SQL: SQL is the lingua franca of data analysis. Business analytics professionals use SQL queries to extract and analyze data from transaction databases and to develop visualizations.
  • Statistical languages: Business analysis professionals frequently use R for statistical analysis and Python for general programming.
  • Statistical software: Business analytics professionals frequently use software such as SPSS, SAS, Sage, Mathematica, and Excel to manage and analyze data.

Business Analytics Dashboard Components

According to analytics platform company OmniSci, the main components of a typical enterprise analytics dashboard include:

  • Data aggregation: Before data can be analyzed, it must be gathered, organized and filtered.
  • Data mining: Data mining sorts large datasets using databases, statistics, and machine learning to identify trends and build relationships.
  • Association and sequence identification: Predictable actions performed in association with other actions or sequentially should be identified.
  • Text mining: Text mining is used to explore and organize large unstructured data sets for qualitative and quantitative analysis.
  • Forecast: Forecasting analyzes historical data from a specific time period to make predictive educated guesses of future events or behavior.
  • Predictive analytics: Predictive business analytics uses a variety of statistical techniques to create predictive models that extract information from data sets, identify patterns, and provide a predictive score for a range of organizational outcomes.
  • Optimization: Once trends are identified and forecasts are established, simulation techniques can be used to test best-case scenarios.
  • Data visualization: Data visualization provides visual representations of tables and graphs for quick and easy data analysis.

Business Analyst Salaries

Here are some of the most popular job titles related to business analysis and the average salary for each position, according to data from PayScale:

  • Analytical Manager: $71,000 to $132,000
  • Business analyst: $48,000 to $84,000
  • Business Analyst, IT: $51,000 to $100,000
  • Business intelligence analyst: $52,000 to $98,000
  • Data analyst: $46,000 to $88,000
  • Market research analyst: $42,000 to $77,000
  • Quantitative Analyst: $61,000 to $131,000
  • Research Analyst, Operations: $47,000 to $115,000
  • Senior Business Analyst: $65,000 to $117,000
  • Statistician: $56,000 to $120,000



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Lance B. Holton