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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.

Peloton & Qlik: The Analytics of It All

Ok, I’ll admit it… I’m one of those people, I own a Peloton – and it’s awesome. But, as a data professional, I’ve struggled with getting decent metrics about how I’m doing and trying to see if I’m making progress with my fitness level. How can I discern performance stats to answer basic questions to gauge my performance over time?

Top 5 Questions about Apache NiFi

Over the last few weeks, I delivered four live NiFi demo sessions, showing how to use NiFi connectors and processors to connect to various systems, with 1000 attendees in different geographic regions. I want to thank you all for joining and attending these events! Interactive demo sessions and live Q&A are what we all need these days when working remotely from home is now a norm. If you have not seen my live demo session, you can catch up by watching it here.

Automated business monitoring: Why you need it now

One of the things we've done a lot of work on at Yellowfin is automated business monitoring (ABM), specifically with our product Yellowfin Signals. It can truly transform organizations and help them to deliver insights faster, ones they can react on. ABM has been in the market for about five years but we haven't seen it take off just yet. One reason is that automated business monitoring challenges the status quo of the data analyst.

A Three-Step Plan to Innovate Hadoop for the Cloud

How large is your Hadoop data lake? 500 terabytes? A petabyte? Even more? And it is certainly growing, bit by bit, day after day. What began as inexpensive big data infrastructure now demands ever more expenditures on storage and servers while becoming increasingly unwieldy and expensive to manage. Such rapacity makes it ever harder to realize a proper return on investment from that Hadoop infrastructure.