Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. In our current landscape, businesses that have adopted a successful ML strategy are outperforming their competitors by over 9%. The implications of ML on the future of business are clear. However, only 4% of enterprise executives today report seeing success from their ML investment.
With a new year ahead, it’s time for financial services to pause, take stock of the “new normal,” and plan a path forward. COVID-19 forced nearly every industry to adapt to a new reality, and the financial services industry was no exception. Consumer habits shifted drastically. Suddenly, many people started working from home. Employee and customer needs changed. Adaptability was a necessity.
In 1969, my aunt graduated from university and joined IBM, the dominant player in the nascent tech industry at the time. She remained at “Big Blue” where she met and married my uncle, and rose up through the management ranks, until their joint semi-retirement exactly 30 years later. She recently told me, “the only way you could get fired in those days was to murder someone, embezzle or steal”.
The Cloudera Data Platform (CDP) represents a paradigm shift in modern data architecture by addressing all existing and future analytical needs. It builds on a foundation of technologies from CDH (Cloudera Data Hub) and HDP (Hortonworks Data Platform) technologies and delivers a holistic, integrated data platform from Edge to AI helping clients to accelerate complex data pipelines and democratize data assets.
Almost a year into the pandemic, the accelerated digital transformation has begun to feel less abrupt and more sustained. 2021 looks likely to be defined by a new phase: Thriving on digital transformation, rather than just surviving through it. We’ve written about the changes forced on the traditionally risk-averse insurance industry by COVID-19.
Needless to say, 2020 was an unforgettable year in a lot of ways and we were all happy to say goodbye to it. The pandemic has ushered in new ways of how we conduct businesses, remote work cultures, telehealth, grocery/food deliveries, etc. While certain industries were hard-hit by this change, most of the businesses were able to adapt, pivot, and take on this adversity in their stride.
In the previous blog post, we looked at some of the application development concepts for the Cloudera Operational Database (COD). In this blog post, we’ll see how you can use other CDP services with COD. COD is an operational database-as-a-service that brings ease of use and flexibility to Apache HBase. Cloudera Operational Database enables developers to quickly build future-proof applications that are architected to handle data evolution.
When Kudu was first introduced as a part of CDH in 2017, it didn’t support any kind of authorization so only air-gapped and non-secure use cases were satisfied. Coarse-grained authorization was added along with authentication in CDH 5.11 (Kudu 1.3.0) which made it possible to restrict access only to Apache Impala where Apache Sentry policies could be applied, enabling a lot more use cases.
Cloudera Operational Database is now available in three different form-factors in Cloudera Data Platform (CDP). If you are new to Cloudera Operational Database, see this blog post. And, check out the documentation here. In this blog post, we’ll look at both Apache HBase and Apache Phoenix concepts relevant to developing applications for Cloudera Operational Database.
