Advancing through the digital era with a greater use of self-service analytics doesn't mean that you have to trash proven analytics tools and techniques.
Data quality, data privacy, and advanced technologies such as AI, machine learning, neural networks, and more, are of top concern to data analytics pros and IT managers, says Karen Lopez, Data & Analytics Track Chair for Interop ITX 2018. Read More
Enterprise software development teams have historically had trouble ensuring the code that runs well on a developer's machine also runs well in production. DevOps has promoted more collaboration between developers and IT operations. Data scientists and data science teams face similar challenges, which DevOps concepts can help address. Read More
Data science techniques are getting better, cheaper, and easier to use. Even small and medium sized organizations can now tap these technologies. But, if you fail to properly introduce, support, and integrate data science capabilities, a lot of money can be wasted. Read More
As we enter a new year of technology planning, find out about the hot technologies organizations are using to advance their businesses and where the experts say IT is heading. Read More
Before you decide which way to take your analytics career in 2018, take a look at this slideshow, highlighting the highest-paying job titles for data analytics professionals. Read More
