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Understanding BI Tools in Today’s Market

Smarten

Without business intelligence, the enterprise does not have an objective understanding of what works, what does not work, and how, when and where to make changes to adapt to the market, its customers and its competition. This approach typically focuses on descriptive analytics based on historical data to answer the question “What happened?”

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. What are the benefits of business analytics? What is the difference between business analytics and business intelligence? Business analytics techniques.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more. What are the four types of data analytics? In business analytics, this is the purview of business intelligence (BI).

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics. Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes.

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

Note how this simple mathematical expression of prescriptive analytics is exactly the opposite of our previous expression of predictive analytics (given X, find Y). Here are a few business examples of this type of prescriptive analytics: Which marketing campaign is most efficient and effective (has best ROI) in optimizing sales?

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Python for Business: Optimize Pre-Processing Data for Decision-Making

Smart Data Collective

Besides, libraries like Pandas and Numpy make Python one of the most efficient technologies available in the market. Besides, Python allows creating data models, systematizing data sets, and developing web services for proficient data processing. Data Preprocessing is a Requirement. Somewhat becomes slow in computation.