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8 data strategy mistakes to avoid

CIO Business Intelligence

“Establishing data governance rules helps organizations comply with these regulations, reducing the risk of legal and financial penalties. Clear governance rules can also help ensure data quality by defining standards for data collection, storage, and formatting, which can improve the accuracy and reliability of your analysis.”

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

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15 Best Data Analysis Tools You Can’t Miss in 2022

FineReport

Most data analysts are very familiar with Excel because of its simple operation and powerful data collection, storage, and analysis. Key features: Excel has basic features such as data calculation which is suitable for simple data analysis. Price: Excel is not a free tool. From Talend.

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What is a Data Pipeline?

Jet Global

Batch processing pipelines are designed to decrease workloads by handling large volumes of data efficiently and can be useful for tasks such as data transformation, data aggregation, data integration , and data loading into a destination system. What is the difference between ETL and data pipeline?

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.