Evaluate

Evaluate

Weigh the pros and cons of technologies, products and projects you are considering.

• Data modeling software tackles glut of new data sources

  Data modeling platforms are starting to incorporate features to automate data-handling processes, but IT must still address entity resolution, data normalization and governance. Continue Reading

• Find the best data integration tools for your organization

  Read analysis and comparisons of data integration tools to help you select the right platform from the leading commercial and open source products currently on the market. Continue Reading

• 4 factors to consider in a Hadoop distributions comparison

  Examine the key characteristics necessary to evaluate in a Hadoop distribution comparison, focusing on enterprise features, subscription options and deployment models. Continue Reading

• Investigate Hadoop distributions for your organization

  Hadoop distributions help organizations manage mass volumes of data. It is important to research options, features and vendors before you make a final buying decision. Continue Reading

• Navigate the data integration product buying process

  Companies require a data integration product to help manage the constant influx of data. This buyer's guide walks through all the cases to consider before buying one. Continue Reading

• Evaluate the features of data integration tools and software

  Before you evaluate and select data integration tools and software, assess which must-have, should-have and nice-to-have features match your organization's needs.Continue Reading

• Data integration platforms take users beyond ETL software

  Discover how commercial data integration platforms help organizations manage and simplify the process of combining and sharing their increasing volumes of data.Continue Reading

• Google Cloud Spanner overview: 4 features to consider

  Cloud Spanner's ability to offer data consistency and horizontal scalability has helped the relational database service gain traction. Learn more about its architecture.Continue Reading

• Augmented data management draws more enterprise interest

  With AI and machine learning, organizations are starting to augment their data management. This is changing the way enterprise users capture, govern and integrate data.Continue Reading

• Explore Hadoop distributions to manage big data

  Discover the uses of Hadoop distributions and the first steps in evaluating these products, as well as how the merger of rivals Cloudera and Hortonworks affects the market.Continue Reading

• Web integration platform eases way to machine learning models

  StoryFit data scientists employ machine learning algorithms to gauge film script scenarios' prospects. They use Import.io tools to make data preparation easier.Continue Reading

• Cloud data warehouse makes inroads as users spurn admin tasks

  Overlooked in the run-up to Hadoop, data warehouses have found new life off premises. Cloud-based data warehouses find favor with teams that want to reduce warehouse administration.Continue Reading

• 5 data management infrastructure technologies to evaluate

  It's the start of a new year -- is your organization ready to face the data management challenges ahead? Here are five technologies to consider adopting.Continue Reading

• Graph database use cases reveal relationships in data sets

  Graph databases specialize in mapping relationships in data sets, particularly complex ones. We explore how they work and the applications they're suited for.Continue Reading

• Advantages of graph databases: Easier data modeling, analytics

  Graph databases are finding a place in analytics applications at organizations that need to be able to map and understand the connections in large and varied data sets.Continue Reading