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Many people may know me as someone who aims to find a mathematical angle in almost everything. And they wouldn’t be wrong – on my journey to bring my passion for math to the masses, I’ve even shown the mathematical angle for finding love! Yes, really – feel free to read my book on it. So, if there’s just one thing that I want people to take away from my chat with Joe DosSantos on Data Brilliant, it’s that math and data really do touch every part of our lives.

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. This year, we expanded our partnership with NVIDIA, enabling your data teams to dramatically speed up compute processes for data engineering and data science workloads with no code changes using RAPIDS AI.

When digital disruption first hit the finance and investment markets, it seemed to signal the death knell for the traditional banks and financial institutions. For a time, it looked as though the best-known brands were doomed to become utilities: only good for basic financial transactions, weighed down by legacy processes and technologies, and viewed as little more than digital dinosaurs.

84.51° is a wholly owned subsidiary of Kroger, the US retailing giant – the largest supermarket chain in America, and the fifth-largest retailer in the world. As an organization, 84.51° is a descendant of dunnhumby, analytics geniuses who revolutionized customer loyalty programs at Tesco in the UK decades ago.

Companies deal with high volumes of data every day. In fact, 51% of businesses realize a positive difference in their bottom line by using their business intelligence (BI) to predict customer trends. According to one source, the BI market may reach close to $30 billion before the end of 2022. With so much money going into data management and so much resulting from it, the need for effective cybersecurity measures continues to grow by the day.

This article is the second in a multipart series to showcase the power and expressibility of FlinkSQL applied to market data. In case you missed it, part I starts with a simple case of calculating streaming VWAP. Code and data for this series are available on github. Speed matters in financial markets. Whether the goal is to maximize alpha or minimize exposure, financial technologists invest heavily in having the most up-to-date insights on the state of the market and where it is going.

Prior the introduction of CDP Public Cloud, many organizations that wanted to leverage CDH, HDP or any other on-prem Hadoop runtime in the public cloud had to deploy the platform in a lift-and-shift fashion, commonly known as “Hadoop-on-IaaS” or simply the IaaS model.