Analytics for Change How Networks and Data Science Will Revolutionize Organizational Change

whitePaper | February 24, 2022

Today’s business relies on access to critical data more than ever to remain ahead of the competition. Due to the challenges over the last two years, organizations must respond to greater demand for data access and a shift to supporting AI/ML in a complex, hybrid multi-cloud environment. Organizations need to become nimble in providing fast, reliable access to data anytime, anywhere, throughout their increasingly complex, integrated enterprise.

whitePaper | February 19, 2020

Artificial Intelligence is developing fast. It will change our lives by improving healthcare (e.g. making diagnosis more precise, enabling better prevention of diseases), increasing the efficiency of farming, contributing to climate change mitigation and adaptation, improving the efficiency of production systems through predictive maintenance, increasing the security of Europeans, and in many other ways that we can only begin to imagine. At the same time, Artificial Intelligence (AI) entails a number of potential risks, such as opaque decision-making, gender-based or other kinds of discrimination, intrusion in our private lives or being used for criminal purposes.

whitePaper | August 2, 2022

The volume of data has exploded across all sectors in the last decade. Enterprise data has grown enormously, and organizations must contend with more unstructured data than ever. In fact, 95 percent of businesses cite the need to manage unstructured data as a challenge.

whitePaper | August 25, 2022

Most organizations realize data governance is necessary - if not indispensable - for mitigating data risk while sustaining its longterm value. However, there’s still a fair amount of ambiguity around what exactly data governance is and how to best implement it. By definition, data governance is an enterprise-wide initiative for formalizing the processes, people, and protocols for using data. It reduces risk while increasing data’s ultimate value: consistent reusability for achieving mission critical objectives. Data governance is a strategic approach for creating unassailable trust in data throughout the enterprise.

whitePaper | June 8, 2023

The importance of data in achieving successful business outcomes cannot be emphasized enough in this digital era. Businesses in recent times have embarked on digital transformation as they strive to keep existing customers happy while creating opportunities for new ones. It is worth noting that investments in data related concepts have soared, making data concepts such as data analytics, machine learning, interpretation of structured and unstructured data highly prevalent as these enable fast decision making for business agility.

whitePaper | January 31, 2020

Many companies have invested heavily in specialized enterprise data warehouses (EDW) and Extract, Transform and Load (ETL) technologies to analyze their operational data. But these technologies were never designed to be truly real-time.They were originally built for batch, and that original design limits how real-timeEDWs and ETL can become. They were also designed to support a focused group ofanalysts, not a larger group of employees spanning operational functions, or even partner and end customers.