Remove 2021 Remove Data Transformation Remove Interactive Remove Visualization
article thumbnail

Introducing Cloudera DataFlow Designer: Self-service, No-Code Dataflow Design

Cloudera

In 2021 we launched Cloudera DataFlow for the Public Cloud (CDF-PC) , addressing operational challenges that administrators face when running NiFi flows in production environments. Developers need to onboard new data sources, chain multiple data transformation steps together, and explore data as it travels through the flow.

Testing 95
article thumbnail

Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Visual layouts in some screenshots in this post may look different than those on your AWS Management Console. You’re now ready to query the tables using Athena.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Showpad accelerates data maturity to unlock innovation using Amazon QuickSight

AWS Big Data

In 2021, Showpad set forth the vision to use the power of data to unlock innovations and drive business decisions across its organization. In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers. Showpad migrated over 70 dashboards with over 1,000 visuals.

article thumbnail

How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

After the data lands in Amazon S3, smava uses the AWS Glue Data Catalog and crawlers to automatically catalog the available data, capture the metadata, and provide an interface that allows querying all data assets. The data products from the Business Vault and Data Mart stages are now available for consumers.

article thumbnail

What Is Embedded Analytics?

Jet Global

This is in contrast to traditional BI, which extracts insight from data outside of the app. We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Plus, there is an expectation that tools be visually appealing to boot. Their dashboards were visually stunning.