Predictive Intelligence Only Works With High Quality Data
Poor data quality leads to several other intangible losses such as customer dissatisfaction, less effective decision-making, and the reduced ability to execute …
Topic: Big Data
Big Data technologies and use cases for real-time analytics. Big Data technologies, market insights, and use cases for real-time analytics.
The Business Value of Intelligent Data Pipelines
Intelligent data pipelines serve as a transformative solution for organizations seeking to stay competitive in an increasingly data-driven
DataOps’ Role in a Modern Data Pipeline Strategy
Increasingly, businesses are using DataOps principles to guide their data pipeline strategies, construction, and operations.
All Diamonds, No Rough: Don’t Overlook Data Quality During a Migration
The quality of your data determines the success of your migration. So, part of the process is finding your outdated, irrelevant, and duplicated data so that …
Data Residency: Meeting the Demands of Today’s Global Landscape
Selecting a cloud provider that offers data residency has become essential to manage today’s global data environment.
Data Pipeline Pitfalls: Unraveling the Technical Debt Tangle
Technical debt in the context of data pipelines refers to the compromises and shortcuts developers may take when building, managing, and maintaining the …
Speed To Market Issues Lead Big Data-as-a-Service Market Growth
Big data as a service is expected to see major growth in market size over the next decade, fueled by organizations automating data
DataOps Trends To Watch in 2023
DataOps is becoming critical for organizations to ensure that data is being used in an efficient and compliant
What Are Data Contracts? And Should You Use Them?
Data contracts may soon be a common feature of the modern data organization. They are one tool in a growing arsenal of solutions to data-related challenges …
Transformation Drivers: Innovative Data Management Tools and New Skillsets
Most organizations are learning quickly that data is the main pillar of any transformation. That makes data management all the more important.