With thousands of tables and scripts in siloed sources, connecting the data to leverage its business value has become a significant issue. Machine Learning data catalogs (MLDC) solve this challenge, help enterprises recover control of their data, and ensure that users can quickly access data for queries and produce reports that can be trusted.

We are excited to announce GenoPalate, an innovator and leader in the growing nutritional genomics field, has selected us as its new tech partner. By utilizing genetics and nutritional science, GenoPalate has made it their mission to improve its customers' health by providing personalized nutrition and food recommendations based on the individual's DNA. 

Event messaging in the 1990s revolutionized enterprise-to-customer communication and connections. However, now the event messaging systems of old can’t keep up with cloud-era needs for data streaming and message volume in the billions across IoT devices distributed worldwide. Enter Solace, the creator of a lightning-fast, real-time event messaging platform for the digital age.

TESCHGlobal forms partnership with Solace to enable integration of real-time, event-driven messaging architecture for modern analytics, hybrid cloud and IoT strategies.

Automated Machine Learning platform – and new TESCHGlobal partner – DataRobot changes all the AI, Machine Learning, and Predictive Analytics problems facing organizations today. By packaging data science, user-friendly functionality, and rapid deployment options, DataRobot makes AI far more accessible to organizations of all shapes and sizes and accelerates speed to value.

TESCHGlobal forms partnership with DataRobot to advance integration of automated machine learning in analytics transformation.

Artificial intelligence (AI) technology has evolved to the point where companies can effectively use it for customer service. In fact, the second most common use of AI right now is in service automation. In our near future, it’s likely that around 85% of all customer service interactions without a human customer service representative (CSR).

Sophisticated, mature data visualization understanding takes time for most business intelligence analysts to achieve. One of the most important factors to keep in mind is data visualizations are intended to engage users and deliver true insights for greater business transparency. These actionable take-aways, lessons, and “ah-ha!” moments are the lynchpin for successful deployment and ROI.

One of the most powerful steps organizations can take today to modernize their business intelligence (BI) capabilities is integrating predictive analytics. Predictive analytics is a practice that encompasses a variety of statistical techniques that analyze current and historical facts to make predictions about future or otherwise unknown events.

As a development platform for data management, Talend was already in a class by itself before its recent update. With 1,091 existing connectors, it can ingest almost any kind of data. Talend 7.0.1 adds features and functionality that everyone can get excited about, from the occasional user to the CIO. Check out the latest and greatest.

While Tableau has made continuous improvements over the years in Tableau Desktop’s ability to connect to, reformat, and integrate data, Tableau Prep combines those capabilities – and more – in a more robust, visual, and easy-to-use package. To understand how Tableau Prep can help you quickly and confidently combine, shape, and clean your data, we walked through a case study in the context of recent school performance, enrollment, staffing, discipline, crime rates, and other factors surrounding the Parkland school shooting in Florida on February 14th, 2018.

Many decision makers who are responsible for the quality, security, and accessibility of business data today are faced with the following question: is now the time to invest in a cloud data warehouse? In this conclusion to a 5-part “how to” blog series, VP of Product Delivery Josh Dodge provides a quick recap to review key steps needed to make educated financial decisions when migrating to the cloud.

The term data lake has become a catch-all for any data management concept that doesn’t fit into data warehousing, and unfortunately, it gets a bad rap when the Big Data BI strategies it can support may not live up to their potential. Gartner estimates that 85% of Big Data projects fail, and according to Gartner's Nick Heudecker, “The problem isn't technology.”

Do you have a web application that’s outgrowing MySQL, an open-source relational database management system? Your team may want to consider Amazon Aurora, a cloud-hosted, plug-in replacement for MySQL and PostgreSQL that offers better performance, scalability, and is more cost effective. 

Despite its complexity, data in modern healthcare comes down to something we all learned in kindergarten: Sharing is good. Data sharing is the common thread running through every interaction between patients, providers and payers, uniting them in a value-based approach that has potential to lower healthcare costs, improve healthcare quality and outcomes, and create a more patient-centered care experience.

As Jeanne Ross of MIT puts it, “A digital transformation involves rethinking the company’s value proposition, not just its operations.” These days it’s rare to find a company that doesn’t have some type of digitization underway to reduce costs and improve operations. The new challenge for companies is digital transformation.

Elasticity can dramatically lower total cost of ownership (TCO) by allowing you to pay for only what you use when you need it, and radically boost performance on demand by scaling the environment to meet the demand of your queries at run-time. Therefore, it is very important to evaluate this aspect of any cloud data warehouse provider.

Whether you are a Tableau developer-in-the-making, a Server administrator getting up to speed, or a would-be recipient of published content, a short but uphill climb into the awesome world of Tableau awaits.