Accountability and Traceability White Paper & Research Roadmap

April 18, 2023

The MIT Future of Data Initiative is leading a multi-disciplinary research agenda to design and stimulate the deployment of consumer-empowering and accountable systems to provide trusted, traceable uses of personal data on an ecosystem-wide scale. The Initiative has gathered together computer science and Internet policy researchers as well as leading commercial enterprises in financial services, payment technology, cloud platforms, insurance and other sectors to discuss current challenges and opportunities in privacy and data governance. Today’s modern privacy laws place appropriately high expectations on organizations processing personal data. At the same time, consumers report declining trust in those who handle their personal data and regulators around the world struggle with the scale of the enforcement challenge. We aim to identify and put into service technical infrastructure for enterprises seeking to handle personal data in a trustworthy and lawful manner with guardrails to enable the traceable, accountable, and scalable use of data.

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Pragmatix Services

Pragmatix Services is a Business Intelligence & Analytics firm focussed on providing solutions and services across multiple functional areas such as customer retention and profitability, sales force effectiveness and productivity, fraud identification and prevention, product functionality and marketing effectiveness, payments spend, risk management, operational efficiency and risk analytics. Over 25 Global & Regional Clients in Banking & Financial Services, Telecom & Retail segments leverage our cutting edge BI & Analytics capabilities to improve their business outcomes in Sales, Marketing, Compliance, Risk Management, Finance & Human Resources. Our Industry leading platform Vital Analytix is a Business Intelligence (BI) tool used in identifying, extracting and analyzing business data. It provides historical, current and predictive views of business operations. Vital Analytix performs data analysis over a data mart created specifically for a business need to optimize the performance. T

OTHER WHITEPAPERS

Why Multi-Cloud is Imperative to Any Modern Data Strategy

whitePaper | September 7, 2022

Today, organizations are increasingly seeking technologies that simplify the deployment of their application workloads in a multi-cloud design to get lower TCO, build best-of-breed solutions, and avoid vendor lock-in. Whether to optimize the costs of running and managing private cloud or to enable developer velocity to efficiently build the modern, intelligent applications of tomorrow, the benefits of multi-cloud offerings are an attractive proposition for enterprises.

7 Trends for Data Science in 2021

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.

Enterprise Data Orchestration

whitePaper | June 3, 2021

Data growth continues at an exponential rate even as cloud architectures make data management more complex and advanced applications necessitate more data movement. So what can be done to enable clean data capture and movement across an enterprise? Read this white paper to learn the requirements for data orchestration at scale and discover how you can build a holistic data architecture that enables successful DataOps.

Top considerations for cloud native databases and data analytics

whitePaper | October 1, 2021

centering your database and data analytics workload development and deployment on a Kubernetes-based container, you can create a more efficient and speedy data life cycle. Access this white paper to learn how to improve key capabilities for database and data analytics workloads across hybrid cloud environments.

Build Modern Data Streaming Analytics Architectures on AWS

whitePaper | December 1, 2022

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Introducing Apache Druid

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.

Business Intelligence, Big Data Management

Accountability and Traceability White Paper & Research Roadmap