With over 150,000 customers, Salesforce remains the world's No.1 customer relationship management (CRM) platform. No other CRM comes close. However, there are some things Salesforce can't do. If you want to align customer data with your marketing objectives, you might integrate Salesforce with a platform like HubSpot, Marketo, or Zoho. Unfortunately, that's easier said than done. Below, learn the challenges of syncing Salesforce data with marketing platforms and how ETL provides a solution.

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.

If you are new to creating pivot tables within Google sheets, this step-by-step guide will help you understand the basic concepts.

In the ever-changing world of technology, the tools available to citizen integrators are constantly evolving as well. For citizen integrators, access to better low-code integration tools certainly makes their job much easier. However, with the industry landscape constantly changing, it can be difficult to keep up with all the latest trends and find the right low-code integration tools to best meet the needs of the company.

With each passing year, companies are becoming increasingly more dependent on APIs. Essentially, any organization looking to take advantage of the latest cloud technologies is dependent on APIs. Therefore, understanding how APIs work and how to best manage APIs is crucial. However, tackling APIs alone can be quite challenging for many companies.

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?

Machine learning (ML) model serving refers to the series of steps that allow you to create a service out of a trained model that a system can then ping to receive a relevant prediction output for an end user. These steps typically involve required pre-processing of the input, a prediction request to the model, and relevant post-processing of the model output to apply business logic.