Features

Features

• Mixed metadata, master data management process a must for mobile apps

  The growing use of mobile devices by business users broadens the risk of data inconsistencies, a hazard that an integrated process for managing metadata and master data can help address.  Continue Reading

• Building a data lake takes meticulous planning -- and flexibility

  Data lakes offer a more expansive alternative to data warehouses for analytics uses. TDWI analyst Philip Russom offers advice on how to get things right in a data lake architecture.  Continue Reading

• Q&A: Big data leads to bad insights without a data governance plan

  Big data holds the potential to provide invaluable insights for business growth, but only if data governance is part of the plan.  Continue Reading

• TDWI finds big data approaches that move jobs from POC to production

  Big data approaches outlined in a TDWI maturity model help bridge the chasm between proof of concept and production. One finding: Stick-to-itiveness is a key to success.  Continue Reading

• Data ingestion capabilities augur greater role for NoSQL in IoT

  Verizon's ThingSpace IoT platform uses a Couchbase NoSQL system to help provide reliable data ingestion and flexible development. That is key as IoT devices proliferate.  Continue Reading

• McKesson looks to simplify big data ecosystem for healthcare analytics

  The big data ecosystem has many twists and turns. A McKesson data manager saw Splice Machine's database as a means to straighten the path by putting analytics and operations data in one place.  Continue Reading

• A look at the leading operational database management systems

  The market for operational DBMS products can be confusing, especially with so many choices. But knowing your application requirements can help point you in the right direction.  Continue Reading

• Preparing data for analysis helps JTV find predictive gold

  Predictive models help Jewelry Television's on-air hosts sell its wares, thanks to data integration and preparation processes that funnel a mix of data into the analytics applications.  Continue Reading

• Data preparation steps increase to meet predictive analytics needs

  Data scientists building predictive models and machine learning algorithms often have to do more data preparation work upfront than is necessary in conventional analytics applications.  Continue Reading

• Fast-moving big data changes data preparation process for analytics

  Increased automation of data pipelines and more flexibility for data scientists through self-service software are taking hold as big data deployments change data preparation practices.  Continue Reading

• With better scaling, semantic technology knocks on enterprise's door

  Cambridge Semantics CTO Sean Martin says better scalability can lead to richer representations of data. Such advances are behind the renewed interest in semantic technology.  Continue Reading

• Embedded analytics to feel widest impact of machine learning projects

  Ovum analyst Tony Baer discusses machine learning tools, IoT-driven streaming analytics and Hadoop in the cloud, all of which gained attention in 2016, with more likely in store for 2017.  Continue Reading

• Microsoft SQL Server 2016 relational DBMS overview

  Microsoft SQL Server 2016 for Windows comes in four editions, with updates that include a new stretch database feature, Polybase, dynamic data masking and more.  Continue Reading

• A look at the EnterpriseDB Postgres data management platform

  The EDB Postgres platform, which is based on the PostgreSQL open source relational database, is offered as a subscription service for production and nonproduction systems.  Continue Reading

• Inside the Amazon DynamoDB NoSQL cloud database as a service

  The DynamoDB NoSQL cloud database supports both document and key-value store models, providing flexibility for development of web, gaming, IoT and many other applications.  Continue Reading