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When companies work with data that is untrustworthy for any reason, it can result in incorrect insights, skewed analysis, and reckless recommendations to become data integrity vs dataquality. Two terms can be used to describe the condition of data: data integrity and dataquality.
Now, almost any company can build a solid, cost-effective data analytics or BI practice grounded in these new cloud platforms. eBook 4 Ways to Measure DataQuality To measure dataquality and track the effectiveness of dataquality improvement efforts you need data.
It’s critical that business analysts have the data they need and that IT has the appropriate metadata associated with those datasets for seamless replication into the cloud. That’s why a data catalog is critical to any organization – particularly if you run analysis and reports in clouddata platforms.
Cloud Adoption Will Continue Steadily Cloud computing and its inherent scalability and elasticity offer distinct advantages, especially with respect to AI/ML and advanced analytics. As clouddata platforms and powerful analytics tools gain in popularity, the march toward the cloud continues at a rapid pace.
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