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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets.

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What is business intelligence? Transforming data into business insights

CIO Business Intelligence

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was.

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

This has led to the emergence of the field of Big Data, which refers to the collection, processing, and analysis of vast amounts of data. The term “Big” does not only refer to its size, but also to its capacity to acquire, organize, and process information beyond the capabilities of traditional databases.

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Incorporating Artificial Intelligence for Businesses : The Modern Approach to Data Analytics

BizAcuity

Enterprise Artificial intelligence (AI) is a common jargon used to refer to how an organization integrates artificial intelligence (AI) into its infrastructure to drive digital transformation. Artificial Intelligence Analytics. Just another important tech jargon, APIs are short for Application Programming Interface.

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What Is Embedded Analytics?

Jet Global

Bottom line is that analytics has migrated from a trendy feature to a got-to-have. Plus, there is an expectation that tools be visually appealing to boot. In the past, data visualizations were a powerful way to differentiate a software application. Their dashboards were visually stunning. It’s all about context.

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Using IBM Watson to Answer Two Important Questions about your Customers

Business Over Broadway

IBM Watson Studio is an end-to-end analytics solution to help you gain insights from your data. Watson Studio accomplished this feat by providing a platform to help you prepare data and build models on your own desktop using their easy-to-use visual drag and drop tools. Case Study: The Survey Data. The next step is to analyze the data.