Remove Big Data Remove Data mining Remove Optimization Remove Structured Data
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Transforming Big Data into Actionable Intelligence

Sisense

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

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Here’s How To Implement Manufacturing Analytics Today

Smart Data Collective

Big data is everywhere , and it’s finding its way into a multitude of industries and applications. One of the most fascinating big data industries is manufacturing. In an environment of fast-paced production and competitive markets, big data helps companies rise to the top and stay efficient and relevant.

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Understanding Structured and Unstructured Data

Sisense

Structured vs unstructured data. Structured data is far easier for programs to understand, while unstructured data poses a greater challenge. However, both types of data play an important role in data analysis. Structured data. Structured data is organized in tabular format (ie.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

Data governance principles According to the Data Governance Institute, eight principles are at the center of all successful data governance and stewardship programs: All participants must have integrity in their dealings with each other.

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Business Intelligence Solutions: Every Thing You Need to Know

FineReport

Business intelligence can assist decision-making and operation optimization, either at the operational or tactical, or strategic levels. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. Data preparation and data processing.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users. Dig into AI.