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• 5 best practices for managing real-time data integration

  Real-time data integration isn't like traditional data integration -- "it's moving, it's dirty and it's temporal," cautions one data pro. Experts offer up some best practices. Continue Reading

• Evolving data integration strategies target new analytics needs

  Most companies don't have a shortage of data, but it's often stored in siloed systems or inconsistent formats -- problems that data integration programs need to address. Continue Reading

• What goes into a customer analytics data integration framework

  Customer data integration is a minefield for IT teams to navigate. But incorporating a set of core technical functions into an integration architecture can ease the process. Continue Reading

• Expert: For BI, you must know the data integration process

  Understanding the data integration process is central to self-service BI and data architecture design, consultant Rick Sherman says in an end-of-year look at data management trends. Continue Reading

• Data management processes take on a new tenor in analyst's view

  Changes in data management processes -- including self-service data preparation, data lakes and real-time analytics -- create a new landscape in companies, according to analyst Matt Aslett. Continue Reading

• Big data makes data preparation steps more complicated to navigate

  The data preparation process is becoming harder to manage effectively, especially for big data analytics applications involving large amounts of data from a variety of sources.Continue Reading

• Big data teams get proactive on data preparation for analytics users

  Organizations with big data environments are starting to prepare data for analysis before making it available to data scientists and other users, instead of leaving the work to them.Continue Reading

• Big data poses weighty challenges for data integration best practices

  Big data architectures are complicating the data integration process for more and more IT teams, driving them to hit the gas on efforts to expand their integration capabilities.Continue Reading

• Data integration framework needs more horsepower to handle big data

  Big data architectures are complicating the data integration process for more and more IT teams, driving them to hit the gas on efforts to expand their integration capabilities.Continue Reading

• Metadata management tools help data lake users stay on course

  Effective metadata management processes can prevent analytics teams working in data lakes from creating inconsistencies that skew the results of big data analytics applications.Continue Reading

• Streaming, connectivity new keys to data integration architecture

  The growing use of the cloud, big data and data from outside sources has complicated data integration, making the addition of data streaming and broader connectivity a must.Continue Reading

• Cross-platform integration, data preparation process grows in cloud

  While cloud computing may be convenient and more cost-effective for users, it can also lead to new challenges and requirements in regard to integrating and processing data.Continue Reading

• Don't throw out design principles when jumping in Hadoop data lake

  In a Q&A, data warehousing expert Joe Caserta explains why a new generation of developers building Hadoop clusters and other big data systems may need an introduction to some fundamental rules of ETL.Continue Reading

• Solid data integration techniques pave clear path for info

  Implementing an effective data integration strategy is becoming increasingly important as organizations look to collect and analyze information from a diverse set of data sources.Continue Reading

• Self-service data preparation tools tap into machine learning

  Machine learning is a hot technology in analytics applications -- and it also underpins new data preparation tools that let business analysts and users integrate data for analysis.Continue Reading