BARC Score Enterprise BI & Analytics Platforms

August 12, 2021

This BARC Score report will evaluate BI & analytics platforms on a range of features, from data visualization capabilities to semantic modeling abilities, performance and speed to automation capabilities.

Spotlight

Quantifind

Quantifind helps some of the world’s biggest banks catch money laundering and fraud. Quantifind also works with government agencies to use the same platform to uncover criminal networks and combat election tampering. Unlike other players in this space, Quantifind delivers results as software-as-a-service (SaaS) with consumer-grade user experiences. Quantifind is a data science technology company whose AI platform uncovers signals of risk across disparate and unstructured text sources. In financial crimes risk management, Quantifind’s solution uniquely combines internal financial institution data with public domain data to assess risk in the context of Know Your Customer (KYC), Customer Due Diligence (CDD), Fraud Risk Management, and Anti-Money Laundering (AML) processes. Today these compliance processes are burdened by ever-increasing regulatory responsibilities and an expectation of frictionless transactions. Legacy technologies demand increasingly more human resources as the oper

OTHER WHITEPAPERS
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Why Open Architectures Matter in BI: A White Paper on Openness

whitePaper | September 1, 2022

Lock-in occurs when the cost or effort of moving away from a particular choice (platform, vendor) outweighs the benefit of doing so, even if that choice is good for the business overall. The pain of moving is simply too great to consider doing it.

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The Rising Threat to Consumer Data in the Cloud

whitePaper | December 29, 2022

Imagine that you are starting a family and you want to stay on top of your finances so you can manage your budget for your growing family. Because you have too many accounts for banking, loans, subscriptions, and bills to keep track of, you decide to sign up for a service that aggregates all your accounts in one place. When you register your account online, you follow the instructions carefully. You create a strong, unique password and set up multifactor authentication. You enter your bank account and loan information, home address, and other personal information. Your spouse also signs up, and you create a joint family account that combines your information.

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Four Reasons Your Metadata Is Broken

whitePaper | April 1, 2021

Metadata is more important now than ever. New technologies have enabled businesspeople who have traditionally not been analysts to work with data. The consumerization of IT means people expect systems to be intuitive and require little training. With so many people using data to support so many kinds of decisions, it’s critical that your data is described, defined, and understood.

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Accountability and Traceability White Paper & Research Roadmap

whitePaper | 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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Building a Data Management Strategy for Your Nonprofit

whitePaper | June 14, 2022

In a digital-first world, every organization needs a data management plan. Yet, fewer than 25% of nonprofits report having a plan in place. This means data is infrequently shared across departments and rarely used to make decisions or predict future stakeholder behaviors. A data management plan is fundamental to make an impact and an attainable goal regardless of organization sizeor technological capacity. An effective data management plan takes into account your mission, staffing, time, budget, goals, existing technology, and more.

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The Evolution of Clinical Data Management into Clinical Data Science

whitePaper | September 12, 2022

Clinical Data Management (CDM) evolved over the last two decades from managing data entered on paper Case Report Forms (CRFs) to managing data transcribed into Electronic Data Capture (EDC) systems. The Society for Clinical Data Management (SCDM) strongly contributed to this first significant CDM evolution through its Good Clinical Data Management Practice 1 (GCDMP©) Chapters first published in 2000 and its certification program for Clinical Data Managers2 subsequently released in 2004.

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Spotlight

Quantifind

Quantifind helps some of the world’s biggest banks catch money laundering and fraud. Quantifind also works with government agencies to use the same platform to uncover criminal networks and combat election tampering. Unlike other players in this space, Quantifind delivers results as software-as-a-service (SaaS) with consumer-grade user experiences. Quantifind is a data science technology company whose AI platform uncovers signals of risk across disparate and unstructured text sources. In financial crimes risk management, Quantifind’s solution uniquely combines internal financial institution data with public domain data to assess risk in the context of Know Your Customer (KYC), Customer Due Diligence (CDD), Fraud Risk Management, and Anti-Money Laundering (AML) processes. Today these compliance processes are burdened by ever-increasing regulatory responsibilities and an expectation of frictionless transactions. Legacy technologies demand increasingly more human resources as the oper

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