Tips

Tips

• Expert urges data pros to hone data science skills

  IT expert William McKnight shares job tips for data professionals looking to prosper in a changing enterprise. His first piece of advice: continually foster data science skills.  Continue Reading

• 5 tips for migrating to BI in the cloud without overpaying

  Moving BI and analytics to the cloud requires a strategy to avoid excessive costs. Get tips from experts and IT pros on what to watch out for and what to address.  Continue Reading

• Better sentiment analysis can bolster customer data analytics

  Customer data analytics are easy to gather in the social media era -- but they can be misleading if based on sentiment analysis culled from automated social media monitoring.  Continue Reading

• How to make a self-service BI tools deployment less painful

  Self-service BI can be a big change for everyone in an organization. Expert Rick Sherman offers three principles to keep in mind that could make things easier.  Continue Reading

• 5 self-service BI best practices for larger organizations

  Self-service analytics programs can streamline the BI process by allowing users access to data, but scaling out to thousands of users requires proper planning.  Continue Reading

• Data silos can live or die by a self-service BI strategy

  Self-service BI is a driving force behind the reshaping or possible demise of data silos. But sound data governance and corporate attitude adjustments are needed first.  Continue Reading

• Rules change for self-service BI subscription pricing models

  As self-service BI tools become commonplace, look for subscription pricing models to change according to the cloud, group data usage pricing and how people share their data.  Continue Reading

• 10 dos and don'ts for deploying self-service BI tools

  Self-service BI doesn't just happen. Organizations must ensure data quality and watch how analysts work. Experts offer 10 tips for enabling a self-service culture.  Continue Reading

• 10 features to look for in visualization tools for big data

  Big data is meaningless if it isn't understandable. Experts explain why users need data visualization tools that offer embeddability, actionability and more.  Continue Reading

• 6 big data visualization project ideas and tools

  These data visualization project examples and tools illustrate how enterprises are expanding the use of "data viz" tools to get a better look at big data.  Continue Reading

• 10 tips for implementing visualization for big data projects

  Organizations need to keep users and design at the forefront when launching data visualization efforts, according to experts. Find out why colors and sizing matter.  Continue Reading

• Choosing the best visualization tools for big data analytics

  Data-driven enterprises use visualization tools to tell the stories hidden in big data -- stories which help users turn information into profit. Here's how to choose the right tool.  Continue Reading

• 3 ways to make machine learning in business more effective

  Dun & Bradstreet analytics exec Nipa Basu offers three tips on how to integrate machine learning tools into business processes to help drive better decision-making.  Continue Reading

• Four challenges to successful predictive analytics models

  Analyzing customer interactions to create a predictive analytics model isn't foolproof. Expert David Loshin shares four factors that could stymie your efforts.  Continue Reading

• Building a data science team in today's data-centric climate

  Finding and training data scientists to build a data science team can be challenging. But in a recent webinar, a Gartner analyst offered tips on how to do it.  Continue Reading