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Analytics

3 types of data models and when to use them

Data modeling is the process of organizing your data into a structure, to make it more accessible and useful. Essentially, you’re deciding how the data will move in and out of your database, and mapping the data so that it remains clean and consistent. ThoughtSpot can take advantage of many kinds of data models, as well as modeling languages. Since you know your data best, it’s usually a good idea to spend some time customizing the modeling settings.

Automated Financial Storytelling at Your Fingertips: Here's How

Every financial professional understands that the numbers matter a great deal when it comes to reporting financial results. Accuracy, consistency, and timeliness are important. Those same professionals also know that there’s substantive meaning behind those numbers and that it’s important to tell the stories that lend additional depth and context to the raw financial statements.

Choosing The Best Approach to Data Mesh and Data Warehousing

Data mesh is being talked about a lot to describe the way data is managed across the organization. But what does it really mean for your organization’s data management strategy and how can its framework support your business needs and drive data pipeline success? On a high level, data mesh is about connecting and enabling data management across distributed systems.

Neustar Sets A New Bar For Accuracy In The Field Of Identity Resolutions

In this episode of “Powered by Snowflake” host Daniel Myers queries the mind of Neustar’s Head of Product and Customer Intelligence, Ryan Engle. Neustar is an Identity Resolutions Platform, responsible for powering more than 90% of caller ID in the United States. This conversation covers fascinating topics such as the challenges of sharing customer data in a highly regulated industry, how the Native Application Framework allows Neustar to work directly within their clients’ environments, and how Snowflake “auto-magically” keeps data fresh and up to date.

Universal Data Distribution with Cloudera DataFlow for the Public Cloud

The speed at which you move data throughout your organization can be your next competitive advantage. Cloudera DataFlow greatly simplifies your data flow infrastructure facilitating complex data collection and movement through a unified process that seamlessly transfers data throughout your organization. Even as you scale. With Cloudera DataFlow for Public Cloud you can collect and move any data (structured, unstructured, and semi-structured) from any source to any destination with any frequency (real-time streaming, batch, and micro-batch).

Alloy DB Demo - Integrate.io

AlloyDB stands out among cloud databases with its higher scalability, 99.99% availability SLA, and full integration with Google’s suite of AI/ML products—which allow it to deliver the best of the cloud to its customers. One AlloyDB use case involves migrating on-premises or self-managed PostgreSQL—or other hosted cloud-based databases—to AlloyDB. Watch this simple demo on how to achieve this migration easily with Integrate.io ETL.

Qlik Expands Google BigQuery Solutions, Adding Mainframe to SAP Business Data for Modern Analytics

In April this year, we announced that Qlik had successfully achieved Google Cloud Ready – BigQuery Designation for its Qlik Sense® cloud analytics solution and Qlik Data Integration®. We continue increasing customer confidence by combining multiple Qlik solutions alongside Google Cloud BigQuery to both help activate SAP data, and now mainframe data as well.