What is data preparation?
Good data preparation gives efficient analysis, limits errors and inaccuracies that can occur to data during processing, and makes all processed data more accessible to… Read More »What is data preparation?
Home » Archives for Vanitha
Vanitha
What is data governance?
Data governance is the process of managing the datas usability, security, availability, and integrity within an organization using internally set and enforced rules and policies.… Read More »What is data governance?
What is a Data Mesh?
Data mesh is an architectural paradigm that unveils analytical data at scale, rapidly releasing access to an increasing number of distributed domain data sets for… Read More »What is a Data Mesh?
What is a Data Fabric?
Gartner says a data fabric is a custom-made design that provides reusable data services, pipelines, semantic tiers, or APIs via a combination of data integration… Read More »What is a Data Fabric?
Data Quality and DataOps towards Customer Value
Data is an essential topic in todays business world. Every business owner wants to talk about innovative ideas and the value that can flow from… Read More »Data Quality and DataOps towards Customer Value
Understand Your Data Better with Agile Data Governance
Agile Data Governance is the process of improving data assets by iteratively capturing knowledge as data producers and consumers work together so that everyone can… Read More »Understand Your Data Better with Agile Data Governance
7 Reasons why you need data integration strategy
Data integration is defined as gathering data from multiple sources to create a unified view. The process of the consolidated data avails users with consistent access… Read More »7 Reasons why you need data integration strategy
7 Reasons why you need a data integration strategy
Data integration is defined as gathering data from multiple sources to create a unified view. The process of the consolidated data avails users with consistent access… Read More »7 Reasons why you need a data integration strategy
Introducing the Pillars of Data Observability
Data observability is an integral part of the DataOps process. It helps to reduce errors, the elimination of unplanned work, and the reduction of cycle time. It… Read More »Introducing the Pillars of Data Observability
Say goodbye to traditional data cleansing
Data Cleansing and analysis are the first steps in managing the quality of data. Cleansing is the process of correcting and detecting inaccurate data from… Read More »Say goodbye to traditional data cleansing