Snowflake met with Jan Doumen, Head of Expertise for Allianz Benelux, and Naveed Memon, Program Director, Data and Analytics for Emirates, at Data Cloud Summit 2020. Read excerpts from the conversation to learn how capturing data insights in the Data Cloud brings value to their businesses. Data’s value in the 21st century is often compared to oil’s value in the 18th century. It can transform organizations, opening doors to unprecedented opportunities.
Imagine you’re going through immigration at the airport. The immigration officer says, “I don’t need your passport because I trust that you are who you claim to be.” Wait, what? That would never happen, right? That’s because trust is exploitable. Sooner or later, somebody will try to lie about who they are, and thus a criminal could enter the country. That’s why countries must enforce some form of identity, like a passport, to certify travelers are who they claim.
We are living in a time where a difference of a mere couple of seconds can make you lose your business to another company with a faster, more easily accessible web application. In such a highly competitive space, it is important to squeeze out the maximum amount of performance from your application’s software stack and hardware infrastructure.
Democratization of data within an organization is essential to help users derive innovative insights for growth. In a big data environment, traceability of where the data in the data warehouse originated and how it flows through a business is critical. This traceability information is called data lineage. Being able to track, manage, and view data lineage helps you to simplify tracking data errors, forensics, and data dependency identification.
The importance of effective data analytics within an organization is widely accepted by business leaders at this point. With use cases for data analysis spanning every department—from IT management, financial planning, marketing analytics, and so on—the right data analytics tools can have a significant impact on a company’s profitability and growth.
Five differences between Stitch, Talend, and Xplenty: Organizations store data in many destinations, making that data difficult to analyze. Legacy systems, SaaS locations, in-house databases, apps, you name it — by storing data in all kinds of places, companies can complicate data analytics considerably. Storing data in a warehouse or a lake makes more sense.
Cloudera Operational Database is now available in three different form-factors in Cloudera Data Platform (CDP). If you are new to Cloudera Operational Database, see this blog post. And, check out the documentation here. In this blog post, we’ll look at both Apache HBase and Apache Phoenix concepts relevant to developing applications for Cloudera Operational Database.