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Rethinking ‘Big Data’ — and the rift between business and data ops

CIO Business Intelligence

When it broke onto the IT scene, Big Data was a big deal. Still, CIOs should not be too quick to consign the technologies and techniques touted during the honeymoon period (circa 2005-2015) of the Big Data Era to the dust bin of history. Data is the cement that paves the AI value road. Data is data.

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How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

The data collected in the system may in the form of unstructured, semi-structured, or structured data. This data is then processed, transformed, and consumed to make it easier for users to access it through SQL clients, spreadsheets and Business Intelligence tools. Big data and data warehousing.

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How The Cloud Made ‘Data-Driven Culture’ Possible | Part 1

BizAcuity

2005: Microsoft passes internal memo to find solutions that could let users access their services through the internet. 2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. Amazon launches AWS (but no cloud solutions yet).

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

In this traditional architecture, a relational database is used to store data from streaming data sources. Datasets used for generating insights are curated using materialized views inside the database and published for business intelligence (BI) reporting.

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Modernize Using The BI & Analytics Magic Quadrant

Rita Sallam

Like when Oracle acquired Hyperion in March of 2007, which set of a series of acquisitions –SAP of Business Objects October, 2007 and then IBM of Cognos in November, 2007. decline in traditional BI ( See: Market Share Analysis: Business Intelligence and Analytics Software, 2015 ).

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Data Science, Past & Future

Domino Data Lab

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Then in the bottom tier, you had your data management, your back office, right? That was the origin of big data. Then things changed.