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.

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.

When we talk about a healthy lifestyle, we know it takes more than diet and exercise. A lifelong practice of health requires discipline, logistics, and equipment. It is the same for data health: if you don’t have the infrastructure that supports all your health programs, those programs become moot.

CDP (Cloudera Data Platform) Private Cloud 1.2 was recently released and builds on the success of CDP Private Cloud Base (see the 7.1.6 release blog). While Private Cloud Base is the ideal modernization of both CDH and HDP deployments for traditional workloads, Private Cloud adds cloud-native capabilities.

Making a decision on a cloud data warehouse is a big deal. Beyond there being a number of choices each with very different strengths, the parameters for your decision have also changed. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

Today, data is constantly growing in complexity and quantity. Ensuring your users consistently find reliable answers from their dashboards and reports for informed decision-making can be difficult if you don't actively guide them on on how to optimally use the analytics tools you provide. However, the challenge is exacerbated by the fact most BI solutions on the market today still tailor their tools to experienced analysts first.