A Business Guide to Modern Predictive Analytics

whitePaper | August 10, 2022

Connected Data, though used synonymously with Big Data, is carefully created and curated for storage and reference during the customer’s lifetime. As we already know, enterprises need to carefully build and store Big Data to avoid creating a data swamp. Connected Data goes a step ahead of Big Data. It is customer-specific data built in a context-sensitive framework to ensure a 360-degree view of the customer profile, purchasing habits, preferences, etc., at a glance.

whitePaper | June 27, 2023

Data mesh is an innovative approach to data management that offers a solution to the most common challenges organizations face when dealing with large-scale data management. Data mesh concept consists of four key principles for large-scale data management in a multi-tiered, multi-domain organizational structure: domainoriented ownership, data as product, federated computational governance and a self-service data platform. These all promote a more agile, efficient and scalable data architecture. However, one of the central challenges to implementing data mesh is designing decentralized governance mechanisms that align with its core principles.

whitePaper | August 23, 2022

Digital transformation has moved businesses from a mode of retrieving and organizing critical information in conventional data stores to a new goal: capturing and storing every bit that passes through the business. The number and diversity of data sources are constantly expanding. New horizons are recognized in data as a raw resource with potential for value creation, even if specific points of value cannot yet be discerned.

whitePaper | August 25, 2022

This paper discusses how hybrid cloud and data analytics together enable new business value to be created in financial services organisations, proposes ways in which analytics can be embedded successfully and outlines how Atos, Microsoft and Dell EMC are collaborating to help bring these advantages about.

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 | October 20, 2022

Data governance defines how data should be gathered and used within an organization. Download this whitepaper to understand how it's linked to business success.