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Data Lifecycle Management

Data Lifecycle Management focuses on data governance, data cleansing and quality, and data stewardship. The rubric applies to articles that focus primarily on the high-level preparation, flow, and use of data through an organization, rather than with one single facet such as storage or analysis.

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Cloud Computing Services, Features and Benefits

  • DineshBhol 

Cloud computing services have grown in popularity significantly over the years. Many sectors are moving to cloud computing services for business operations. Cloud computing enables businesses to store, manage, and process essential data using remote servers hosted on the internet.

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Want Greater Business Efficiency? Map Your Smart Data Transformation Journey

  • Jodi Daniels 

Companies need to collect huge volumes of data produced to extract valuable insights via data analysis to survive, let alone thrive in the competitive marketplace. It is the lifeblood of most business decisions, functions, and processes. But the process of data collection can be highly challenging for many organizations.

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What is trustable data? Why do you need it?

  • Vanitha 

Trustable data can be defined as data that comes from specific and trusted sources and is used according to its intended use. It is delivered in the appropriate format and time frames for specific users.

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Best practices to maintain high data quality

  • Vanitha 

With the world’s data multiplying in leaps and bounds, every organization is trying to make better business decisions in marketing, product development, and finance using insights from the data they hold. The value of businesses today can be measured by the quality of the data they hold.

Digital transformation conceptual for next generation technology

Challenges and Best Practices of Data Cleansing

  • Vanitha 

Data accuracy is the biggest challenge many businesses encounter in their quest to cleanse data. Having accurate data is the foundation of the usefulness of data in all its stages of use.

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