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Advanced Analytics: If You Don’t Know What You Need, How Can You Succeed?

ElegantJ BI

Requirements Planning for Data Analytics Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. If you select the right solution, you can ensure data and personal security and provide appropriate access at all levels of the organization.

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Advanced Analytics: If You Don’t Know What You Need, How Can You Succeed?

ElegantJ BI

Requirements Planning for Data Analytics Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. If you select the right solution, you can ensure data and personal security and provide appropriate access at all levels of the organization.

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Advanced Analytics: If You Don’t Know What You Need, How Can You Succeed?

ElegantJ BI

Requirements Planning for Data Analytics. One of the crucial success factors for advanced analytics is to ensure that your data is clean and clear and that your users have a good understanding of the source of the data so that they can put results in perspective. Data Governance and Self-Serve Analytics Go Hand in Hand.

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Data Modeling: Techniques, Best Practices, & Why It Matters?

Astera

Data modeling is the process of structuring and organizing data so that it’s readable by machines and actionable for organizations. In this article, we’ll explore the concept of data modeling, including its importance, types , and best practices. What is a Data Model?

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The Best Fivetran Alternatives in 2024

Astera

So, in this article, we will explore some of the best alternatives to Fivetran. As far as the destinations are concerned, Fivetran supports data warehouses and databases, but it doesn’t support most data lakes. It also offers limited data transformation capabilities and that too through dbt core, which is an open source tool.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

Data Pine

Engineered to be the “Swiss Army Knife” of data development, these processes prepare your organization to face the challenges of digital age data, wherever and whenever they appear. Data quality refers to the assessment of the information you have, relative to its purpose and its ability to serve that purpose.

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How to: Focus on three areas for a holistic data governance approach for self-service analytics

Tableau

Editor’s note: This article originally appeared on CIO.com. If we asked you, “What does your organization need to help more employees be data-driven?” where would “better data governance” land on your list? A data governance framework. Identify root causes of data governance to drive impactful change.