In this contributed article, Colin Kessinger. Executive Partner at Ethos Capital, touches on why data curation needs to be a priority. He discusses why data lakes ultimately end up being a burden – and addresses the misconception that once data is stored, it is inherently useful – along with the differences between curation and governance.
Introducing The Streaming Datalake
February 2, 2024 by
In this contributed article, Tom Scott, CEO of Streambased, outlines the path event streaming systems have taken to arrive at the point where they must adopt analytical use cases and looks at some possible futures in this area.
Navigating Data Lake Challenges: Governance, Security, and GDPR Compliance
September 7, 2023 by
In this contributed article, Coral Trivedi, Product Manager at Fivetran, discusses how enterprises can get the most value from a data lake. The article discusses automation, security, pipelines and GSPR compliance issues.
Why Do We Prefer ELT Rather than ETL in the Data Lake? What is the Difference between ETL & ELT
July 4, 2023 by
In this article, Ashutosh Kumar discusses the emergence of modern data solutions that have led to the development of ELT and ETL with unique features and advantages. ELT is more popular due to its ability to handle large and unstructured datasets like in data lakes. Traditional ETL has evolved into cloud-based ETL which allows rapid batch processing, scalability, savings, and simplicity while maintaining security, governance, and compliance.
Video Highlights: Modernize your IBM Mainframe & Netezza With Databricks Lakehouse
November 3, 2022 by
In the video presentation below, learn from experts how to architect modern data pipelines to consolidate data from multiple IBM data sources into Databricks Lakehouse, using the state-of-the-art replication technique—Change Data Capture (CDC).
Maximizing Data Lake Utility with Query Optimization
July 14, 2022 by
In this contributed article, editorial consultant Jelani Harper highlights the recent acquisition of Varada by Starburst in terms how the deal provides Starburst’s platform two pivotal benefits. On the one hand, it employs cognitive computing to intelligently index data at scale. On the other, it has caching capabilities that make queries even more responsive for swiftly retrieving answers for informed decision-making, analytics, and applications.
From Data Warehouses and Data Lakes to Data Fabrics for Analytics
December 3, 2021 by
In this contributed article, Kendall Clark, Founder and CEO of Stardog, discusses how data fabric is fast-becoming the data architecture foundation for analytics and how it is revolutionizing the $50 billion data lakes/warehouse market. Supported by real-word examples, the article explores how technologies such as expressive semantic modeling, knowledge graph, and data virtualization are connecting disparate data lakes to streamline data pipelines, reduce dataops costs and improve analytics insight.
HPC as a Service to Accelerate Transformational Growth
September 24, 2021 by
[SPONSORED POST] This whitepaper discusses how HPC delivered as a service through HPE GreenLake combines the power and compliance of on-premises systems, with cloud-like financial flexibility, ease of management, and consumption-based pricing. HPE managed services and support help accelerate HPC time to value. Without upheaval, customers get a smoother, faster path to better business through HPC.
HPC as a Service to Accelerate Transformational Growth
September 15, 2021 by Leave a Comment
This whitepaper discusses how HPC delivered as a service through HPE GreenLake combines the power and compliance of on-premises systems, with cloud-like financial flexibility, ease of management, and consumption-based pricing. HPE managed services and support help accelerate HPC time to value. Without upheaval, customers get a smoother, faster path to better business through HPC.
Data Warehouse Costs Soar, ROI Still Not Realized
August 28, 2021 by
Enterprises are pouring money into data management software – to the tune of $73 billion in 2020 – but are seeing very little return on their data investments. According to a new study out from Dremio, the SQL Lakehouse company, and produced by Wakefield Research, only 22% of the data leaders surveyed have fully realized ROI in the past two years, with most data leaders (56%) having no consistent way of measuring it.
