Operational Database is a relational and non-relational database built on Apache HBase and is designed to support OLTP applications, which use big data. The operational database in Cloudera Data Platform has the following components: Atlas provides open metadata management and governance capabilities to build a catalog of all assets, and also classify and govern these assets. The SDX layer of CDP leverages the full spectrum of Atlas to automatically track and control all data assets.

At Singular, we have a pipeline that ingests data about ad views, ad clicks, and app installs from millions of mobile devices worldwide. This huge mass of data is aggregated on an hourly and daily basis. We enrich it with various marketing metrics and offer it to our customers to analyze their campaigns’ performance and see their ROI. The upshot is that we receive tens of thousands of events per second and handle dozens of terabytes of data every day, managing a data set of several petabytes.

The phenomenon of web-based, at-your-door-in-minutes, restaurant food-delivery service is widespread and commonplace nowadays, with various apps and platforms, such as Grubhub or DoorDash, providing diners with an at-home eating experience – look up a restaurant, choose what you want to eat, and your food is on its way. The same can be said about grocery shopping.

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way.

Gift guides come in all shapes and sizes. There are shopper’s guides for sporting goods and wine, aimed at travelers and crafty types, and offering electronics or candy. Since there is no gift guide we’re aware of for data buyers, this is our chance to create the first such guide. Is your wife, best friend, or dad a nerd? No, not that kind of nerd, not an over-the-counter nerd, a data nerd! If so, this stuff will stuff their stocking but good. Remember Sears’ Wish Book?

This week, ThoughtSpot gathered virtually with thousands of global customers, partners, and friends to share our vision for the future of analytics at Beyond 2021. A future where everyone in your business can create personalized insights and operationalize them to drive smarter business actions. And where innovative brands like Snowflake, Starbucks, Just Eat Takeaway, and Opendoor are already building their businesses on data with the Modern Analytics Cloud.

We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. But, we also know that experimentation alone doesn’t yield business value. Organizations need to usher their ML models out of the lab (i.e., the proof-of-concept phase) and into deployment, which is otherwise known as being “in production”.

Snowflake is the data backbone for thousands of businesses, enabling data access and governance needed to deliver value. Interactive use cases in some data applications and embedded analytics, however, pose a particular challenge. Traditionally, you needed an additional caching layer to provide the required speed and throughput these solutions require—which also increased costs and architectural complexity.

A look at Qlik Replicate's zero-footprint architecture and how it is designed for scalability and flexibility.

It’s no secret that Data Scientists have a difficult job. It feels like a lifetime ago that everyone was talking about data science as the sexiest job of the 21st century. Heck, it was so long ago that people were still meeting in person! Today, the sexy is starting to lose its shine. There’s recognition that it’s nearly impossible to find the unicorn data scientist that was the apple of every CEO’s eye in 2012.