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McKesson: Using Big Data to Improve Care and Save Lives

Sisense

Disrupting Markets is your window into how companies have digitally transformed their businesses, shaken up their industries, and even changed the world through the use of data and analytics. The use of big data analytics and cloud computing has spiked phenomenally during the last decade.

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Transforming Big Data into Actionable Intelligence

Sisense

As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data. Referring to the conceptual “edge” of the network, the basic idea is to perform machine learning (ML) analytics at the data source rather than sending the sensor data to a cloud app for processing.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data. Referring to the conceptual “edge” of the network, the basic idea is to perform machine learning (ML) analytics at the data source rather than sending the sensor data to a cloud app for processing.

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Top 10 Analytics And Business Intelligence Trends For 2020

Data Pine

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

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What Is Embedded Analytics?

Insight Software

Introduction Why should I read the definitive guide to embedded analytics? But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.

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What is a Data Pipeline?

Insight Software

ETL is a specific type of data pipeline that focuses on the process of extracting data from sources, transforming it, and loading it into a destination, such as a data warehouse or data lake. ETL is primarily used for data warehousing and business intelligence applications.