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AI & Business Analytics: A Smart Guide

Sunflower Lab

Diving into World of Business Analytics Data analytics is not an old concept, it is an essential practice which has driven business success in the past and the present, it will confidently drive the success in the future too.

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How to take machine learning from exploration to implementation

O'Reilly Media - Data

Scalable Machine Learning for Data Cleaning. Over the last few years, many companies have begun rolling out data platforms for business intelligence and business analytics. Can decentralization technologies (like blockchains) pave the way for new forms of data exchanges? Data preparation, governance and privacy".

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Re-Thinking the Storage Infrastructure for Business Intelligence

Infinidat

Re-Thinking the Storage Infrastructure for Business Intelligence. With digital transformation under way at most enterprises, IT management is pondering how to optimize storage infrastructure to best support the new big data analytics focus. Adriana Andronescu. Wed, 03/10/2021 - 12:42.

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Building a Beautiful Data Lakehouse

CIO

Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio. They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. Learn more at [link]. .

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Altexsoft - Untitled Article

Altexsoft

From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. For over 30 years, data warehouses have been a rich business-insights source. Is it still so?

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What Is Cloud Analytics – And Why Should You Use It?

Datavail

Analytics is the process of turning raw data into valuable business insights through quantitative and statistical methods. There are three ways of classifying business analytics methods according to their use case: Descriptive methods examine historical data to identify meaningful trends and patterns.

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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

It has the key elements of fast ingest, fast storage, and immediate querying for BI purposes. These include stream processing/analytics, batch processing, tiered storage (i.e. You can take this knowledge and build a RTDW that is specialized for Time Series and Event Analytics. Flexible, scalable query engine for EDW.

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