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As enterprises become more agile, centralization appears more and more a thing of the past waterfall world. This need is equally true with data platforms. This paradigm drove us to build a Data Mesh, this next generation of data platforms for PayPal Credit. This talk will detail quickly go over the evolution of data platforms, highlight the problems of current data platforms, and explain why we decided to build a Data Mesh. I will detail the four principles of the Data Mesh, how we got started, and describe some current and future challenges and how we plan to solve them. Part of the Expert Hour series.

For a data analyst, financial analytics is one of the most useful skill sets to inculcate given the rapid growth of roles in this booming sector. A specialisation in this field will be a value-add given the rapid rise of fintech in India’s digital ecosystem. Financial analytics helps companies uncover deeper insights into the company’s finances and can help in finding pain points and new streams of revenue. Financial Analysts work in investment firms, banks, insurance sector and digital payments companies.

If you missed out on all the trends for 2019 published in December, or even if you caught some of them, this one merits your time. We’ll be going into 2019 and beyond, since the winners will have an eye on the long view for the source of competitive advantage that is analytics. It is a fascinating, explosive time for enterprise analytics. It is from the position of analytics leadership that the mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.

It can be difficult to scale out relational databases and provide more schema flexibility, thus the rise of NoSQL. However, you shouldn’t have to sacrifice data integrity and transactions in order to scale out on commodity hardware and support semi-structured data. By using an RDBMS with built-in sharding and JSON support, you don’t have to. You get the scalability and flexibility of a NoSQL database along with the consistency and reliability of a relational database – and the ability to mix and match relational and JSON data. In this webinar, we’ll explain how MariaDB Platform can be deployed as a NoSQL database by using the Spider storage engine and built-in SQL functions for JSON. In addition, we’ll discuss how you can access relational data as JSON documents, and how to enforce data integrity if a relational data model is extended with JSON