BIG DATA MANAGEMENT
Katipult | July 06, 2022
Katipult Technology Corp. , a leading Fintech provider of software for powering the exchange of capital in equity and debt markets, announced today that its private placements platform, DealFlow, has been upgraded with the addition of a new enterprise-grade data integration module – DealFlow: DataHub. This module enables users to securely link their backend systems with the DealFlow platform, allowing them to directly populate subscription documents with the latest information from their systems of record.
"We're very excited to announce the launch of the DealFlow: DataHub module. Our experience working with investment banks and broker dealers showed us that being able to seamlessly interface with their legacy systems of record is critical for helping them accelerate the pace of digital transformation. DealFlow:DataHub further amplifies the efficiency-boosting capabilities of DealFlow by removing yet another manual step in the private placements process. Not only is scalability improved, but there are also positive knock-on effects on compliance as data integrity and continuity are preserved."
Gord Breese, Katipult CEO
DealFlow:'s DataHub extracts large volumes of data from the commonly used systems of record in the industry, such as ISM or Dataphile. The data is then streamlined and used to populate the intelligent digital subscription documents that are core to the DealFlow platform. With the addition of DealFlow: DataHub, customers will no longer need to manually input or update the data that will populate the subscription documents. Further, DataHub will also enable single sign-on to the DealFlow platform, allowing users to sign on with their standard enterprise credentials.
Katipult's goal with DealFlow is to help institutions unlock the full potential of private placements by streamlining as many processes as possible. DealFlow: DataHub represents yet another step forward in that direction.
Katipult is a provider of industry leading and award-winning software infrastructure for powering the exchange of capital in equity and debt markets. Our cloud-based platform and solutions digitize investment workflow by eliminating transaction redundancy, strengthening compliance, delighting investors, and accelerating deal flow. Katipult provides unparalleled adaptability for regulatory compliance, asset structure, business model, and localization requirements.
BUSINESS INTELLIGENCE,BIG DATA MANAGEMENT
Privacera | September 12, 2022
Privacera, the unified data access governance leader founded by the creators of Apache Ranger™, today announced the availability of its AWS Lake Formation integration in private preview, which offers complete data governance automation and fine-grained data access for AWS services including Amazon S3, Amazon Redshift and Amazon RDS. Privacera helps enterprise data teams protect sensitive data and enable privacy across all on-premise, hybrid and multi-cloud data sources while reducing time to insights by automating outdated, manual governance processes.
Privacera is expanding its support and native integration for diverse AWS environments with the new AWS Lake Formation integration to simplify data access governance for complex and heterogeneous data lake and data mesh environments by extending Lake Formation enforcement to third-party services like Databricks, enabling additional governance use-cases. With this new integration, organizations will be able to accelerate their migration to the cloud by leveraging Privacera to securely manage data access policies within a single governance platform across diverse on-premise and cloud data sources. This will significantly reduce the efforts around data migrations to the cloud through increased automation and consistent policy management, and the ability to ensure compliance through an open, consistent and proven standard.
"Organizations operate in diverse data ecosystems, and it's becoming increasingly challenging to not only manage the data from a governance perspective, but ensure that organizations are gleaning timely insights securely through appropriate access controls and automation, and that's why Privacera exists," said Privacera CEO Balaji Ganesan. "As an AWS partner, expanding our capabilities with this new integration allows us to deliver a solution that leverages the strengths of both Privacera and AWS Lake Formation, helping organizations with a secure and simple approach to data access while delivering business value."
The latest integration will give users:
A unified data governance strategy including your lake formation data assets
AWS Lake Formation policy enforcement extended to popular data analytics systems like Databricks
An intuitive and easy-to-use interface to build data access policies on top of AWS Lake Formation
Financial services company Sun Life uses Privacera to accelerate AWS migration and unify data access governance and compliance. "Because Apache Ranger is critical to the success of our entire analytics platform, so is Privacera as it allows us to capitalize on existing technology and deliver critical data to our analytic teams quicker," said a Director of Cloud Infrastructure & Operations at Sun Life. "Our goal was to get our data into a data lake as quickly as possible and then apply access rules so approved Sun Life professionals can actually use the data to generate important insights. Requests that used to take three to four weeks to program can now be reacted to in less than two days."
Founded in 2016 by the creators of Apache Ranger™, Privacera's SaaS-based data security and governance platform enables analytics teams to simplify data access, security, and privacy for data applications and analytical workloads. The Privacera platform supports compliance with regulations such as GDPR, CCPA, LGPD, and HIPAA. Privacera provides a unified view and control for securing sensitive data across multiple cloud services such as AWS, Azure, Databricks, GCP, Snowflake, and Starburst. The Privacera platform is utilized by Fortune 500 customers across finance, insurance, life sciences, retail, media, and consumer industries, as well as government agencies to automate sensitive data discovery, mask sensitive data, and manage high-fidelity policies at petabyte scale on-premises and in the cloud.
BIG DATA MANAGEMENT
Arcadia | August 16, 2022
Arcadia, the leading data analytics platform for healthcare and life sciences, today announced its availability through Prognos Marketplace. Prognos is solving for disconnected, siloed data that cannot interoperate and leaves an incomplete view of the patient, including lab results, prescription information, and medical claims. Arcadia is the first source of electronic health record (EHR) data to be included in the platform, delivering deeper clinical insights that will enable Prognos' life science customers to optimize and accelerate therapy strategies.
Arcadia Research Data is built on an active EHRs and claims-based patient population data that feature comprehensive visibility across payers, multiple sites of care, and the entire clinical patient journey.
Prognos Marketplace will enable linking and access to Arcadia's de-identified RWD data to drive insights for life sciences research to improve health/patient outcomes.
"We are pleased to democratize access to health data at scale by joining Prognos' data partner ecosystem. "The clinical information available in our EHR data will enable these organizations to gather deeper, more accurate medical assessments that can accelerate the advancement of new, life-saving therapies to millions of patients."
Jim Robbins, SVP of Life Sciences at Arcadia
"Prognos' life science customers can now include Arcadia's data in their cohort searches and purchase record-level data to inform therapy targeting, map the patient journey, and support therapy launch and commercialization efforts," said Sundeep Bhan, CEO at Prognos Health. "Providing the ability to combine patients' data across all data types including lab, claims, pharmacy, EHR, mortality, and SDoH data is critical to improving patient outcomes."
Connect with Arcadia at ICPE in Copenhagen to learn more about how their data can support biopharmaceutical research.
Prognos Marketplace houses harmonized lab test results from trusted sources integrated with large sources of prescriptions and medical claims. There are more than 200 billion health records for 325 million de-identified patients, with new data sources being added continually. Users can create and refine patient cohorts and then buy healthcare data through a single contract. All data purchased is available on the Datavant token, making it interoperable with other patient-level data that has been tokenized using Datavant.
Arcadia is dedicated to happier, healthier days for all. We transform data into powerful insights that deliver results. Through our partnerships with the nation's leading health systems, payers, and life science companies, we are growing a community of innovation to improve care, maximize value, and confront emerging challenges.
BIG DATA MANAGEMENT
integrate.ai | August 18, 2022
integrate.ai, a SaaS company helping developers solve the world’s most important problems without risking sensitive data, today announces the availability of its privacy-preserving machine learning and analytics platform.
The platform leverages federated learning and differential privacy technologies to unlock a range of machine learning and analytics capabilities on data that would otherwise be difficult or impossible to access due to privacy, confidentiality, or technical hurdles. Traditional approaches to machine learning and analytics require centralization and aggregation of data sources, often necessitating data-sharing agreements and supporting infrastructure. This can present an insurmountable roadblock for the world’s most important data-driven problems, particularly in the healthcare, industrial, and finance sectors, where data custodians must enforce the highest privacy and security standards to ensure regulatory and contractual compliance. With integrate.ai’s solution, collaboration barriers can be broken as data does not need to move. It allows data to stay distributed in its original protected environments, while unlocking its value with privacy-protective machine learning and analytics. Operations such as model training and analytics are performed locally, and only end-results are aggregated in a secure and confidential manner.
“When data can be securely accessed and collaborated upon, we unlock boundless opportunities for life-saving research and innovation. By allowing organizations to work in a federated way, our platform helps reduce cost structure, accelerate progress against product roadmaps and capture new revenue opportunities—all with more speed and flexibility than any other solution on the market. “Business and technology leaders alike increasingly recognize the global shift towards a more distributed paradigm. After serving at the forefront of this shift over the past five years, this platform will continue to grow into a product suite of easy-to-use tools for developers addressing humanity’s greatest challenges.”
Steve Irvine, founder and CEO of integrate.ai
integrate.ai is packaged as a developer tool, enabling developers to seamlessly integrate these capabilities into almost any solution with an easy-to-use software development kit (SDK) and supporting cloud service for end-to-end management. Once integrated, end-users can collaborate across sensitive data sets while data custodians retain full control. Solutions incorporating integrate.ai can serve as both effective experimentation tools and production-ready services.
DNAstack, a company that offers software for scientists to more efficiently find, access, and analyze the world’s exponentially growing volumes of genomic and biomedical data, is using integrate.ai’s product platform to support federated learning in their work in autism. DNAstack leads the Autism Sharing Initiative, an international collaboration to create the largest federated network of autism data, empowering better genetic insights and accelerating precision healthcare approaches.
“Autism is complex and research has shown the value of connecting massive datasets to drive critical insights. Genetic and health datasets are large, sensitive, and globally distributed, making it impossible to bring them all together in one place,” said Marc Fiume, co-founder and CEO of DNAstack. “Federated learning will empower us to ask new questions about autism across global networks while preserving privacy of research participants.”
In the heavily regulated worlds of healthcare, financial services, and manufacturing, roadblocks to collaborating with sensitive data abound – from existing and proposed privacy regulations and intellectual property (IP) concerns to the high cost of centralizing massive datasets. Data science initiatives often fail or never start in the areas where their impact could be most life changing, such as early cancer diagnoses and detections of fraud, underscoring the considerable need for privacy-preserving data analytics solutions. Armed with experience serving enterprises across six industries and the construction of its own data network, which leveraged 20B interactions between businesses and people, integrate.ai enables safe access to sensitive data with developer tools for privacy-safe machine learning and analytics.
integrate.ai is a SaaS company democratizing access to privacy-enhancing technology to help developers solve the world’s most important problems without risking sensitive data. By breaking down collaboration barriers within and between organizations, integrate.ai empowers developers and data teams with the privacy-preserving tools they need to harness collective intelligence. Armed with experience serving enterprises across six industries and the building of its own data network, which leveraged 20B interactions between businesses and people, integrate.ai’s product platform is increasing quality data access in healthcare research, financial services, industrial IoT and manufacturing, process automation, advertising, marketing and more.