Remove Business Intelligence Remove Data Integration Remove Data Quality Remove Data Strategy
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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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Power of ETL: Transforming Business Decision Making with Data Insights

Smart Data Collective

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses.

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How AWS helped Altron Group accelerate their vision for optimized customer engagement

AWS Big Data

This post discusses the journey that took Altron from their initial goals, to technical implementation, to the business value created from understanding their customers and their unique opportunities better. Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices.

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As insurers look to be more agile, data mesh strategies take centerstage

CIO Business Intelligence

The data mesh debate This is not to say that there is a consensus that data mesh is a universal solution. Stakeholders are currently waging an open debate across the industry of centralization versus federated data strategies.

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How to rule your data world: The role of data governance

BI-Survey

Data and data management processes are everywhere in the organization so there is a growing need for a comprehensive view of business objects and data. It is therefore vital that data is subject to some form of overarching control, which should be guided by a data strategy.

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How to Pinpoint Where Your Organization Wins (and Loses) with Data

CIO Business Intelligence

It’s the only way to drive a strategy to execute at a high level, with speed and scale, and spread that success to other parts of the organization. Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy.