Are you struggling to really track lineage?
Date lineage is increasing important to business users looking to understand and trust data. Yet tradtional solutions provide incomplete and inaccurate results
5 critical success factors for streaming data pipelines
Earlier this year, our partner, Syncsort published the results of their 2019 Data Trends survey. A key finding; IT is grappling with data delivery and value Only nine percent of respondents called their organisation very effective at getting value from data, with many struggling to make data accessible to users. What is Data Streaming? Data…
Best Practices for Bringing Mainframe Data to Hadoop
Both mainframe and Hadoop skills are in high demand – bridge the gap and reduce costly, time-consuming data collection and preparation tasks
4 steps to achieving AI leadership
Artificial intelligence and machine learning are the new “big data’ – the hottest topic in analytics and decision making. The premise – that computers that can think and learn, like humans, can replace humans for many tasks.. Projects like driverless cars; the Internet of Things (IoT) – where machines and devices contaminate amongst each other…
Simplify Big Data Development – Design Once, Deploy Anywhere
It’s certainly not a new refrain, but in recent years IT managers are increasingly being told to do more with less – even as the number of new projects and requirements increase. Data is the fuel that powers most new business initiatives, but each project needs a slightly different blend of data sources and data…
Managing the modern data pipeline
A few weeks back I wrote about the emerging role of the data engineer – the group of person’s responsible for delivering the quality data pipelines that enable the data scientist. I followed it up with this tweet – which I believe summaries very consisely the changing reality of big data and advanced analytics 2012…
What is ETL?
ETL defined Extract, Transform and Load or ETL is a standard information management term used to describe a process for the movement and transformation of data. ETL is commonly used to populate data warehouses and datamarts, and for data migration, data integration and business intelligence initiatives. ETL processes can be built by manually writing custom scripts or code, with…
