Analytics

Unlock Marketing Analytics Power with the Snowflake Data Cloud

Over the past two decades, marketers have faced an uphill battle in trying to turn marketing into a fully data-driven discipline. Our challenge is not that we don’t have enough data but that data has been difficult to access and use. Marketing, sales, and product data is scattered across different systems, and we can’t get a complete picture of what is going on in our businesses.

Can you achieve self-service analytics amid low data literacy?

Customers wanting to drive self-service analytics as part of creating a data-driven organization will often ask, “Can we achieve self service analytics, when our work force has low data literacy?” Or they might say they are not ready for self-service analytics, incorrectly thinking they need first to improve data literacy. But the two are inextricably linked. I liken it to teaching a child to read without giving them any books on which to build their skills.

Pillars of Knowledge, Best Practices for Data Governance

With hackers now working overtime to expose business data or implant ransomware processes, data security is largely IT managers’ top priority. And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. Requirements, however, have changed significantly in recent years.

Accelerating Insight and Uptime: Predictive Maintenance

Historically, maintenance has been driven by a preventative schedule. Today, preventative maintenance, where actions are performed regardless of actual condition, is giving way to Predictive, or Condition-Based, maintenance, where actions are based on actual, real-time insights into operating conditions. While both are far superior to traditional Corrective maintenance (action only after a piece of equipment fails), Predictive is by far the most effective.

How to Operationalize Your Data Warehouse

More and more businesses are opting to use data lakes or, more likely, data warehouses these days, which allow them to store, analyze, and utilize their data from one convenient destination. But beyond creating reports and in-depth analytics, how can you truly operationalize your data warehouse into an even more vital part of your business's digital stack? Reverse ETL could provide some opportunities to do just that.

Creating a COD Database

Cloudera Operational Database (COD) is an operational database as a service that brings ease of use and flexibility. Let’s see how easy it is to create a new database! Once you have created your environment, navigate to the COD Web interface. It takes you to the Databases page. Click Create Database, select the applicable environment, provide a name for your database and click Create Database. The creation of your new database is in progress. Once its status becomes Available it is ready to be used.

The San Francisco Municipal Transportation Agency gets riders where they're going, thanks to Talend, Disy, and geospatial data

Every day, hundreds of thousands of residents and commuters in San Francisco, California, use the public transportation services of the San Francisco Municipal Transportation Agency (SFMTA). In addition to the city’s buses, subway system, and famous cable cars, the SFMTA manages comprehensive services including bicycle and e-scooter rentals, as well as permits for road closures.