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K2view Named a Visionary in the 2023 Gartner MQ for Data Integration Tools
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K2view Named a Visionary in the 2023 Gartner MQ for Data Integration Tools
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CIOCoverage: K2view 1 of 10 Best Data Integration Companies in 2023
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K2view Rated "Visionary" in Gartner Magic Quadrant for Data Integration Tools 2023
Gartner names K2view 1 of 3 Visionaries in its latest Magic Quadrant for Data Integration Tools.
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Data Pipeline
April 5, 2022
What is Reverse ETL?
Although data warehouses and lakes are often associated with offline analytics, Reverse ETL can operationalize actionable insights to make a direct and ongoing...
Data Pipelining
January 27, 2022
iPaaS: A Better Approach to the Cloud Data Pipeline
With the rising need for self-service data integration, enterprises require a more effective cloud data pipeline solution. iPaaS, based on data products, is...
Data Pipelining
October 24, 2021
Building a Data Pipeline Architecture for the Enterprise
Building an effective data pipeline architecture is challenging, especially when enterprise requirements – like scale, speed, and security – are taken into...
Data Pipelining
October 7, 2021
What are ETL Tools? Advantages, Disadvantages and Innovations Revealed
Find out how the ETL method of data integration enhances enterprise data pipelines, and how eETL overcomes the most difficult challenges. Learn more here....
Data Pipelining
August 19, 2021
Avoid Data Lake Failures with Data Quality Management Best Practices
The growing dependence on big data is often met with statistics showing that many data lake projects fail because they did not adhere to data quality...
Data Pipelining
August 5, 2021
Data Integration with Data Products Optimizes your Data Pipeline
More than 80% of enterprises consider data integration a critical component in their ongoing business operations, so choosing the right way to integrate data...
Data Pipelining
July 27, 2021
ETL vs ELT vs eETL
What’s the difference between ETL vs ELT – and how does the new approach, “entity-based ETL” (eETL), effectively address their shortcomings?
Data Pipelining
July 20, 2021
Automated Data Preparation – 4 Issues and 4 Answers
Today’s “automated data preparation” tools aren’t really automated. This article discusses 4 key challenges on the road to automation, and 4 ways to overcome...
Data Pipelining
June 23, 2021
7 Data Preparation Steps to Cleaner Data Lakes
The data preparation process is critical, due to the importance of maintaining clean, high-quality data for operational and analytical workloads. Here are 7...
Data Pipelining
June 20, 2021
Your Data Preparation Process Needs Data Fabric, Not Standalone Tools
For your data preparation process, use a data fabric architecture on a Data Product Platform, instead of an assortment of standalone tools.
Data Fabric
June 20, 2021
Prepare Yourself: What is Data Preparation?
Theoretically, data preparation is the process of exploring, combining, cleaning, and transforming raw data into curated datasets for data integration, data...
Data Pipelining
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