Analytics

Work at warp-speed in the BigQuery UI

Data analysts can spend hours writing SQL each day to get the right insights. So it’s crucial that the tools in the Google Cloud Console make that job as easy and as fast as possible. Now, we’re excited to show you how BigQuery’s Cloud Console UI has been updated with radical usability improvements for more efficient work, making it easier to find the data you need and write the right SQL quickly.

Prioritizing Your People with Randy Wigginton of Square | Snowflake Inc.

Randy Wigginton, Director of Platform Infrastructure Engineering at Square talks about what it takes to produce world-changing innovations, how to use data to fully understand your customers, insights into how to compete with tech giants, and much more. Rise of the Data Cloud is brought to you by Snowflake.

Cloudera Flow Management Continuous Delivery while Minimizing Downtime

Cloudera Flow Management, based on Apache NiFi and part of the Cloudera DataFlow platform, is used by some of the largest organizations in the world to facilitate an easy-to-use, powerful, and reliable way to distribute and process data at high velocity in the modern big data ecosystem. Increasingly, customers are adopting CFM to accelerate their enterprise streaming data processing from concept to implementation.

How Infutor Uses the Placekey External Function to Extend the Power of Snowflake

The Snowflake Data Cloud provides the unique ability for anyone to join their own data sets with thousands of live third-party data sets near-instantly, securely, and without moving data. Businesses operating in the Data Cloud gain a huge advantage over their competitors who are stuck in data silos and struggling with stale data sets downloaded from their legacy data providers weeks, months, or years ago.

How Customer Success Managers Drive Digital Transformation

Before the end of the year, I met with Christina McCoy, a Customer Success Manager for our federal region. We discussed some of her observations and proven practices for driving adoption in her accounts. Christina joined Qlik two years ago; she has over five years of CSM experience and is a graduate of Howard University, where she was a pitcher for the Bison’s softball program.

Handling Large Datasets in Data Preparation & ML Training Using MLOps

Data science has become an important capability for enterprises looking to solve complex, real-world problems, and generate operational models that deliver business value across all domains. More and more businesses are investing in ML capabilities, putting together data science teams to develop innovative, predictive models that provide the enterprise with a competitive edge — be it providing better customer service or optimizing logistics and maintenance of systems or machinery.

How to create 3D Body Maps in Yellowfin BI

One particular feature requested by our customers is 3D body mapping, and whether exporting 3D models and utilizing its visualization and filtering can be applied easily. This technical walkthrough shows you how to leverage Yellowfin to integrate 3D models within Yellowfin and then use them to create a fully interactive display in your dashboard.

Good Testing Data is All You Need - Guest Post

Building machine learning (ML) and deep learning (DL) models obviously require plenty of data as a training-set and a test-set on which the model is tested against and evaluated. Best practices related to the setup of train-sets and test-sets have evolved in academic circles, however, within the context of applied data science, organizations need to take into consideration a very different set of requirements and goals. Ultimately, any model that a company builds aims to address a business problem.

7 Best data management tools in 2021

Data is produced and consumed at volumes and speeds which were unimaginable just a decade ago.Top players have taken advantage of this growth. Tapping into data resources for actionable insights - aptly called the new oil - makes data-driven companies dominate their competition. But the proliferation of data can lead to growing pains. Companies find themselves increasingly incapacitated by the vast and messy nature of their in-house data.