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In this blog, we are going to unfold the two key aspects of data management that is DataObservability and Data Quality. Data is the lifeblood of the digital age. Today, every organization tries to explore the significant aspects of data and its applications. What is DataObservability and its Significance?
How to improve data quality Some common methods and initiatives organizations use to improve data quality include: DataprofilingDataprofiling, also known as data quality assessment, is the process of auditing an organization’s data in its current state.
A data quality standard might specify that when storing client information, we must always include email addresses and phone numbers as part of the contact details. If any of these is missing, the client data is considered incomplete. DataProfilingDataprofiling involves analyzing and summarizing data (e.g.
Databricks Databricks is a cloud-native platform for bigdata processing, machine learning, and analytics built using the Data Lakehouse architecture. Delta Lake Delta Lake is an open-source storage layer that provides reliability, ACID transactions, and data versioning for bigdata processing frameworks such as Apache Spark.
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