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Trends in Analytics


Successful Data Lakes: A Growing Trend

Data lakes have been widely misunderstood, but they are now benefiting from new best practices -- helping organizations gain significant value.

Why Data Science Must (And Will) Be Automated

Data science today is extremely labor-intensive. The automated or quasi-automated features widely used in self-service BI aren't commonplace in data science, but Gartner says that's about to change.

Data Scientist Skills for Success

With the increasing demand for data science professionals, what skills are necessary to succeed in our new digital world?

Data Wrangling Versus ETL: What’s the Difference?

Three things that distinguish data prep from the traditional extract, transform, and load process.

Use a Hadoop-based Data Lake to Empower New Best Practices for Business Analytics

To get full business value from big data and other new data sources, many organizations use a data lake atop Hadoop to capture, process, and manage diverse data at scale for business analytics.

The Future of Text Analytics

As enterprises look to put their best foot forward in 2017, many are increasingly turning to text analysis to improve customer experiences and business processes.

The Data-Driven Fascination with Now

Human biases are easily skewed by newer data because it makes up an ever-larger proportion of the data landscape.

Are Hadoop's Best Days Behind It -- Or Still Ahead?

Pessimists are predicting the end of Hadoop -- "peak Hadoop," in the words of one influential analyst. Optimists say Hadoop's future is assured. Who's right?

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