Opinion

Opinion

• 5 trends driving the big data evolution

  The speedy evolution of big data technologies is connected to five trends, including practical applications of machine learning and cheap, abundantly available compute resources.  Continue Reading

• GDPR compliance requirements drive new winds of data privacy

  Hello, GDPR. May 25 is the witching hour for enforcement of the EU's much-discussed GDPR compliance requirements -- and it's a harbinger of more changes to come.  Continue Reading

• U.S. data protection laws fall short in the age of big data

  Data breaches and a history of data abuse led the EU to adopt GDPR, but it might take massive scale data security crises for the U.S. to legislate similar data protection laws.  Continue Reading

• IoT, edge computing spawn new security issues

  As real-time big data increasingly hitches up to internet of things, edge computing power and fog nodes, a whole new layer of security threats emerges.  Continue Reading

• Data managers should study up on GPU deep learning

  As GPU deep learning becomes more common, data managers will have to navigate several new layers of complexity in their quest to build or buy suitable data infrastructure.  Continue Reading

• Machine learning, IoT bring big changes to data management systems

  Companies are using big data systems, deep learning and machine learning techniques to drive software advances. To go even further, their data management systems must also evolve.  Continue Reading

• From all the data chaos emerges big data value

  Businesses spend millions of dollars to collect, mine, prep and analyze data to gain an edge in the marketplace. Yet, they have a hard time determining big data's actual value.  Continue Reading

• A strong metadata management process eases big data woes

  Big data often comes with big data management problems. Clean, well-defined metadata can make the difference in analyzing big data and delivering actionable business intelligence.  Continue Reading

• Digital disruption shapes big data infrastructure, data engineering

  In the face of burgeoning digital disruption, startups and established companies alike are responding with changes to their big data architectures and data engineering processes.  Continue Reading

• Making connections: Big data algorithms walk a thin line

  Big data algorithms are at the heart of some travel snafus of late. Increasingly, data analytics teams need to look deeper into how algorithms work and the data on which they feed.  Continue Reading

• Look for advances in serving the Hadoop data scientist

  To date, the Hadoop data scientist has had to be a superhero, with a mix of data engineering, administration and analysis skills. Self-service tools will change that, but not overnight.  Continue Reading

• Don't wait until it's too late to build a data governance model

  As companies amass data from multiple sources, they lose control over data quality and accuracy. Like it or not, it's time to halt the data free-for-all and apply data governance.  Continue Reading

• Data managers apply data governance principles on the sly

  Data needs to be governed, but data management teams increasingly are approaching governance in subtle ways to avoid being seen by business users as the data police.  Continue Reading

• BI data governance can take lessons from public sector practices

  When it comes to governance of business intelligence data, the private sector can learn valuable lessons from the public sector's data management practices.  Continue Reading

• Database bottlenecks put applications at risk if left untreated

  Slowdowns in database processing can put a big crimp in business applications -- a corporate malady that database performance management tools are designed to help remedy.  Continue Reading