Systems | Development | Analytics | API | Testing

3-Minute Recap: Unlocking the Value of Cloud Data and Analytics

DBTA recently hosted a roundtable webinar with four industry experts on “Unlocking the Value of Cloud Data and Analytics.” Moderated by Stephen Faig, Research Director, Unisphere Research and DBTA, the webinar featured presentations from Progress, Ahana, Reltio, and Unravel. You can see the full 1-hour webinar “Unlocking the Value of Cloud Data and Analytics” below. Here’s a quick recap of what each presentation covered.

Get Ready for the Next Generation of DataOps Observability

I was chatting with Sanjeev Mohan, Principal and Founder of SanjMo Consulting and former Research Vice President at Gartner, about how the emergence of DataOps is changing people’s idea of what “data observability” means. Not in any semantic sense or a definitional war of words, but in terms of what data teams need to stay on top of an increasingly complex modern data stack.

Ep 59: New Zealand's Crown Research Institute CDAO, Jan Sheppard on Treating Data as a Treasure

Treating data as a treasure is a foundational principle for Jan Sheppard, the Chief Data and Analytics officer at New Zealand’s Crown Research Institute of Environmental Science and Research (ESR.) This agency leads ongoing research in public health, environmental health, and forensics for the country of New Zealand. Like many other CDAOs, her role is relatively new. But the unique values she applies to data can be traced back many hundreds of years to the indigenous Maori people of her country. Through her work, Jan recognizes the profound impact data can have on people and their environments for generations to come.

Developing More Accurate and Complex Machine-Learning Models with Snowpark for Python

Sophos protects people online with a suite of cybersecurity products. Hear Konstantin Berlin, Head of Artificial Intelligence at Sophos, explain how the Snowflake Data Cloud helps Sophos increase the accuracy of their machine-learning models by allowing data scientists to process large and complex data sets independent of data engineers. Through Snowpark, data scientists can run Python scripts along with SQL without having to move data across environments, significantly increasing the pace of innovation.

Yellowfin Named Embedded Business Intelligence Software Leader in G2 Fall Reports 2022

Yellowfin has again been recognized in the Leader quadrant in the 2022 G2 Fall Grid Reports for Embedded Business Intelligence (Enterprise and Small Business). This is Yellowfin's 13th quarter in a row to be named a leader in a G2 Grid Report. The Yellowfin team are grateful to our customers for the reviews they have provided for our embedded analytics capability and product suite on G2, a leading business software and service comparison source for trusted user ratings and peer-to-peer reviews.

Webinar: Unlocking the Value of Cloud Data and Analytics

From data lakes and data warehouses to data mesh and data fabric architectures, the world of analytics continues to evolve to meet the demand for fast, easy, wide-ranging data insights. Right now, nearly 50% of DBTA subscribers are using public cloud services, and many are investing further in staff, skills, and solutions to address key technical challenges. Even today, the amount of time and resources most organizations spend analyzing data pales in comparison to the effort expended in identifying, cleansing, rationalizing, consolidating, and transforming that data.

Talend's contributions to Apache Beam

Apache Beam is an open-source, unified programming model for batch and streaming data processing pipelines that simplifies large-scale data processing dynamics. The Apache Beam model offers powerful abstractions that insulate you from low-level details of distributed data processing, such as coordinating individual workers, reading from sources and writing to sinks, etc.

Building an automated data pipeline from BigQuery to Earth Engine with Cloud Functions

Over the years, vast amounts of satellite data have been collected and ever more granular data are being collected everyday. Until recently, those data have been an untapped asset in the commercial space. This is largely because the tools required for large scale analysis of this type of data were not readily available and neither was the satellite imagery itself. Thanks to Earth Engine, a planetary-scale platform for Earth science data & analysis, that is no longer the case.