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ThoughtSpot Success Series #2 - Defining a Use Case

Introducing the ThoughtSpot Success Series! Want to expand your knowledge of ThoughtSpot? Want to learn some great tips and tricks? Join ThoughtSpot's Customer Success team and other users like yourself as we discuss various topics in our new Success Series. In this session, we'll share how to best define your ThoughtSpot use case in your organization to maximize results & align key stakeholders.

How Xplenty Simplifies Heroku PostgreSQL Data Integration

What can you do with data collected on Heroku PostgreSQL? How will you analyze it and integrate it? With Xplenty, of course! Xplenty lets you connect to a PostgreSQL database on Heroku, design a Dataflow via an intuitive user interface, aggregate the data, and even save it back to PostgreSQL on Heroku or other databases and cloud storage services.

Apache Ozone and Dense Data Nodes

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Businesses are also looking to move to a scale-out storage model that provides dense storages along with reliability, scalability, and performance.

Future of Data Meetup: Nice to Meet You, NiFi!

You asked for and we are delivering the third in our “Hello:“ series of introductory “Big Data” topics. Our next meetup covers using Apache NiFi. Lots of people want to be a data scientist... but what good is machine learning, artificial intelligence or advanced analytics if you don’t have data? Getting data is incredibly important, but getting data in real time or near real time helps you give near real time insight.

The 6 Soft Skills Data Engineers Need to Succeed

Soft skills can be almost as important as data engineering skills when you apply for a job. Soft skills can make the difference between stress and efficiency or being unsatisfied with your position and a raise. When data engineers and data scientists earn bachelor’s degrees, they usually take classes in topics like data warehousing, programming languages, machine learning, and data science.