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.

Hope Haven strives to provide shelter and empower the children of Belize for a brighter future. In the case of this Code Camp, our main goal was to focus our efforts on the young women in this area and teach them the basics of this high-demand industry of web development and coding.

The democratization of data has been a core theme of Tableau analytics since its founding. The company’s market leadership stems in large part to its successful development, enhancement, and deployment of tools which enable all types of users to engage, visualize, and understand their data. This innovation and evolution has enabled self-service business intelligence and analytics for a broad swath of non-technical data consumers in organizations large and small.

Snowflake is a data warehouse built for, and in, the cloud. Its unique architecture keeps it free from many of the problems conventional warehouses encounter. It’s revolutionary because it delivers all of the benefits of other warehouses without the complexity.

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 5-part “how to” blog series, VP of Product Delivery Josh Dodge will explore that question by drilling down into performance test design, execution, and evaluation of a cloud data warehouse and why its a viable solution for organizations looking for a more cost-effective option for storing data sources.