FROM BIG DATA TO BIG BUSINESS

whitePaper | May 5, 2021

Over the last decade, interest in the field of data science has not only increased enormously, but has also changed and developed considerably. In view of the new technological advances and the constant growth of data, we expect Data Science to continue to develop strongly in 2021. We have identified 7 trends that will be relevant for the coming year.

whitePaper | November 18, 2022

For decades, the lack of visibility into the health of our data has led to data downtime in companies around the world. When data is missing, inaccurate, or erroneous, data quality initiatives are doomed to fail, leaving enterprises at a privacy compliance and business disadvantage.

whitePaper | September 28, 2022

By building smarter apps and increasing the speed of business insight, application-driven analytics gives you the opportunity to out-innovate your competitors and improve efficiency. However, it does require a shift in the way we think about and deliver analytics.

whitePaper | December 9, 2022

In Data Governance Methodology, we described why a modern active data governance methodology is superior to a traditional top-down methodology and how active data governance is supported by continuous improvement. We also discussed how a data governance process based on continuous improvement is a key component of a DataOps process.

whitePaper | June 3, 2022

Analyzing data has been a unique business activity for at least 5,000 years, and possibly as long ago as 20,000 years. We have come a long way in how we count, summarize, analyze, predict, and prescribe upcoming courses of action in science, business, and all fields of human endeavor. In the past 75 years, the progress in how we analyze data has increased exponentially. We now regularly build analytical models and complete applications that analyze massive amounts of data.

whitePaper | April 19, 2023

Unplanned downtime is one of the most significant pain points for industrial manufacturers today, costing them an estimated $50 billion each year. The risk is even greater for process manufacturing, where a critical equipment failure could result in the loss of an entire batch, environmental hazards, or safety risks. The adoption of digital technologies, such as the industrial internet of things (IIoT), promises to mitigate these threats by forecasting equipment failures and catching faults before they lead to unscheduled shutdowns. However, in practice, several challenges arise when maintenance personnel and operations leaders work to implement an IIoT solution aimed at eliminating unplanned downtime.