We're living in a data-driven age. In every sector, we've seen new companies emerge, executing lightning-fast strategies based on sophisticated analytics. These data mavericks have disrupted and sometimes even devoured their more traditional rivals. To stay afloat, you need a state-of-the-art data infrastructure. That means having the right platforms, the right data pipelines, and the right analytics engines. But when you have all that data, what do you actually do with it?
COVID-19 has forced virtually every industry to embrace an acceleration in digital capabilities. While it can be argued that digital transformation was already underway; it’s hard to dispute that it has accelerated in recent months. A recent McKinsey survey, cited in CRN, shows that worldwide, 58 percent of customer interactions were digital as of July 2020.
In a previous blog post on CDW performance, we compared Azure HDInsight to CDW. In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to EMR 6.0 (also powered by Apache Hive-LLAP) on Amazon using the TPC-DS 2.9 benchmark. Amazon recently announced their latest EMR version 6.1.0 with support for ACID transactions. This benchmark is run on EMR version 6.0 as we couldn’t get queries to run successfully on version 6.1.0.
Public preview of the data lake export feature is now available. Snowflake announced a private preview of data lake export at the Snowflake virtual summit in June 2020. Data lake export is one of the key features of the data lake workload in the Snowflake Data Cloud. The feature makes Snowflake data accessible to the external data lake, and it enables customers to take advantage of Snowflake’s reliable and performant processing capabilities.
Managing online teams has become the new normal! In an online world, how do you give effective feedback, have a difficult conversation, increase team accountability, communicate to stakeholders effectively, and so on? At Unravel, we are a fast-growing AI startup with a globally distributed engineering team across the US, EMEA, and India. Even before the pandemic this year, the global nature of our team has prepared us for effectively leading outcomes across online engineering teams.
Five leading experts share their insights on what’s ahead for the data industry.
Why you should use Fivetran history mode for historical analysis over alternative solutions.
