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How to create 3D Body Maps in Yellowfin BI

One particular feature requested by our customers is 3D body mapping, and whether exporting 3D models and utilizing its visualization and filtering can be applied easily. This technical walkthrough shows you how to leverage Yellowfin to integrate 3D models within Yellowfin and then use them to create a fully interactive display in your dashboard.

Finding digital transformation in high places - how a ski resort improved operational agility and customer experiences

Most blogs in my history are very focused on Industry 4.0’s digital transformation of the manufacturing industry, which in itself is pretty remarkable. By 2025, Industry 4.0 is expected to generate greater than $11 trillion in economic value as connected manufacturing processes, operations and their supply chains become more streamlined, efficient, agile and realize improved productivity, improved uptime and product quality.

Uncover Gold During an Economic Crisis: Five Steps to Monetizing Your Data

Because of the COVID-19 global pandemic, almost every industry is experiencing volatility, risks and changes to buying behavior. Nevertheless, in crisis often comes opportunity and a forcing factor for businesses to redefine themselves. Those looking to innovate after (or even during) this crisis should focus on two key concepts — data monetization and data modernization.

Loading complex CSV files into BigQuery using Google Sheets

BigQuery offers the ability to quickly import a CSV file, both from the web user interface and from the command line: Indeed, try to open this file up with BigQuery: and we get the errors like: This is because a row is spread across multiple lines, and so the starting quote on one line is never closed. This is not an easy problem to solve — lots of tools struggle with CSV files that have new lines inside cells. Google Sheets, on the other hand, has a much better CSV import mechanism.

Talend vs. MuleSoft vs. Xplenty: Which One Does ETL Better?

The key differences between Talend, MuleSoft, and Xplenty: Enterprise data volumes are increasing by 63 percent per month, according to a recent study. Twenty percent of organizations draw from 1,000 or more data sources. How do these companies extract and move all this data to a centralized destination for business analytics? As we know, Extract, Transform, and Load (ETL) streamlines this entire process. But smaller organizations lack the coding skills required for successful implementation.

Brick and Mortar Stores are Now Built Brick by Brick with Digital Insights

In my last three blogs (Get to Know Your Retail Customer: Accelerating Customer Insight and Relevance; Improving your Customer-Centric Merchandising with Location-based in-Store Merchandising; and Maximizing Supply Chain Agility through the “Last Mile” Commitment) I painted a picture that showed an ever-changing landscape in retail, considering that consumers are more in control than ever, mobile (at least somewhat digitally mobile considering the pandemic) and socially connected.

Apache NiFi - the data movement enabler in a hybrid cloud environment

Cloudera provides its customers with a set of consistent solutions running on-premises and in the cloud to ensure customers are successful in their data journey for all of their use cases, regardless of where they are deployed. Cloudera DataFlow provides Apache NiFi in both the Cloudera Data Platform Private Cloud Base (on-premises) and Public Cloud (AWS, Azure, and Google Cloud) products in this hybrid cloud strategy.

Managing Multiple Accounts with Snowflake Organizations Is Now in Public Preview

We are excited to announce that the new Snowflake Organizations feature is now available in public preview. Organizations enable customers to easily manage their data, storage, and compute across multiple Snowflake accounts and even across regions and clouds. Through a new ORGADMIN role, customers can now: We’re excited to hear how you use these new more powerful self-service capabilities to manage your Snowflake Data Cloud.

Credit Suisse AG Names Unravel Data A Disruptive Tech Winner

Unravel Data is a leader in the emerging field of DataOps, going beyond application performance monitoring (APM) to provide AI-powered recommendations for big data and streaming data applications. Now Unravel is being recognized by banking technology innovator Credit Suisse AG in their prestigious Disruptive Technology Recognition (DTR) program.