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What Stands Between IT and Business Success? Data Complexity

CIO Business Intelligence

A real-time data technology stack has to shrink this innovation gap for the business. . Analysts and data scientists need flexibility when working with data; experimentation fuels the development of analytics and machine learning models. Innovation at integration points.

IT 134
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Why You’re Not Ready for Knowledge Graphs!

Ontotext

Data integration If your organization’s idea of data integration is printing out multiple reports and manually cross-referencing them, you might not be ready for a knowledge graph. Experimentation is important, but be explicit when you do. Start with “why?” Don’t fear growth.

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P&G turns to AI to create digital manufacturing of the future

CIO Business Intelligence

It requires taking data from equipment sensors, applying advanced analytics to derive descriptive and predictive insights, and automating corrective actions. The end-to-end process requires several steps, including data integration and algorithm development, training, and deployment. Data and AI as digital fundamentals.

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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

The most successful programs go beyond rolling out tools by establishing governance in citizen data science programs while taking steps to reduce data debt. Citizen data science reduces shadow IT when CIOs promote proactive data governance and establish data integration, cataloging, and quality practices.

IT 137
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Load data incrementally from transactional data lakes to data warehouses

AWS Big Data

In this post, we discuss different architecture patterns to keep data in sync and up to date between data lakes built on open table formats and data warehouses such as Amazon Redshift. Various data stores are supported in AWS Glue; for example, AWS Glue 4.0 Apache Hudi 0.13.0 Delta Lake 2.0.0

Data Lake 111
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Q&A Tuesday: Jonathan Reichental on Digital Transformation and 21st-Century Excellence

Jet Global

The tools for delving deep into the data of the business, identifying patterns, and making predictions on trends are making a real impact. Organizations need to become really comfortable with experimentation. The innovation process, where experimentation might live in an organization, has grown in popularity in the last few years.

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How to Take Back 40-60% of Your IT Spend by Fixing Your Data

Ontotext

Achieving this advantage is dependent on their ability to capture, connect, integrate, and convert data into insight for business decisions and processes. This is the goal of a “data-driven” organization. We call this the “ Bad Data Tax ”.

IT 69