Tag: governance

Feed: Redis Labs. Author: Yossi Gottlieb. Redis Core Team member Madelyn Olson Last week we announced a new light-governance model for the open source Redis project, following Salvatore Sanfilippo’s stepping back from being Redis’s BDFL and sole maintainer. We believe that defining the right model for Redis was an important step, but it’s just as important to get the right people on board the new core team. In order to preserve the spirit of Redis and its unique DNA, we wanted the core team to consist of people who are already committed to and involved with the project. To that ... Read More

Feed: DivvyCloud. Author: Jamie Gale; Managing identity and access in the cloud is a complex problem, far more complex than it is in traditional, on-premise IT environments guarded by an explicit firewall. As the number of data breaches attributed to illicit or improper access continues to grow, it’s clear that this problem is here to stay. But what makes identity and access management (IAM) an ongoing obstacle for many organizations? And what can organizations do to reduce their risk in this capacity? Let’s start with the basics. First and foremost, what is IAM? According to Gartner, IAM is “the discipline ... Read More

Feed: AWS Architecture Blog. We recently released an updated version of the Operational Excellence pillar of the AWS Well-Architected Framework, which includes expanded guidance on operating model, and organizational culture, as well as some other refinements.Gerald Weinberg, in his 1985 book, The Secrets of Consulting, defined The Second Law of Consulting as “No matter how it looks at first, it’s always a people problem.” I appreciate the humor and wit with which he approached software development. Organizations, teams, and team members have always been a significant part of the Operational Excellence (OE) pillar. They now have their own dedicated section ... Read More

Feed: All Oracle Press Releases. Press Release NRI Selects Oracle Dedicated Region Cloud@Customer First customer to adopt new Oracle Cloud offeringWill be used for mission-critical, high-volume business platform to accelerate digital transformation Redwood Shores, Calif.—Jul 8, 2020 Oracle today announced that Nomura Research Institute (NRI) has selected Oracle Dedicated Region Cloud@Customer to run its critical, high-volume business platform used in various industries, including financial, retail, and distribution. NRI will start by moving its SaaS applications for the financial industry, which are used by about 70 percent of the capital markets firms in Japan, from on-premises to an Oracle Dedicated Region ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: itumeleng-monale; Follow @IBMAnalyticsDataOps journey Our data journey with IBM started when needing to respond to regulatory changes. We have since evolved to applying the technology to various business cases; most recently adapting to COVID-19 market conditions and now looking to the future for building new use cases with DataOps and AI. The journey begins with seeking to improve our data management, in the areas of data quality, governance, business reporting and customer experience.  Regulatory market changes The first market force challenges were regulatory -the Basel Committee on Banking Supervision ... Read More

Feed: AWS Big Data Blog. With Amazon Redshift Spectrum, you can query the data in your Amazon Simple Storage Service (Amazon S3) data lake using a central AWS Glue metastore from your Amazon Redshift cluster. This capability extends your petabyte-scale Amazon Redshift data warehouse to unbounded data storage limits, which allows you to scale to exabytes of data cost-effectively. Like Amazon EMR, you get the benefits of open data formats and inexpensive storage, and you can scale out to thousands of Redshift Spectrum nodes to pull data, filter, project, aggregate, group, and sort. Like Amazon Athena, Redshift Spectrum is serverless ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Subin George. Over a period, large organizations have been transformed into disintegrated silos that has grown to be a major impediment to respond to changing market demands with agility. Organizational silos have led to innumerous disconnected policies, systems, processes, standards, teams. In order to sustain in this digital era, it’s imperative for organizations to take a top down enterprise value chain view to continually evaluate its ability to adapt (as well as compete) to changing market demands->change business models and/or objectives->create or optimize processes->design or enhance systems->manage and govern data. Often ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link. Announcement Our supply chain superheroes are needed now more than ever - Upcoming webinar Selected Data Science Programs from Top Universities Featured Resources and Technical Contributions Fourier Series and Differential Equations with applications in R - Part 1 Math vs. Statistics in One Picture 23 sources of data bias for machine learning and deep learning New ... Read More

Feed: The Connector by Workato. Author: Derrick Chin; Many organizations that already rely on an Integration Platform as a Service (iPaaS) to integrate applications and data remain unconvinced of the necessity of using an API management system concurrently. However, both platforms have distinct capabilities and serve separate purposes. So what is the difference between them? API Integration (or iPaaS) vs. API Management Broadly speaking, an iPaaS is a platform that connects any combination of cloud or onsite applications, enabling businesses to bring data from separate applications, systems and warehouses together to create business process workflows.  APIs underpin this process, using ... Read More

Feed: Featured Blog Posts - AnalyticBridge. Author: Elise Devaux. In a general sense, synthetic data is information that is artificially generated, as opposed to collected from the real-world. But it’s important to note that synthetic data is used for a variety of purposes. As a result, there are several types of synthetic data with different properties depending on the use-cases. For instance, one scenario in which companies use synthetic data is the training of AI/ML models. Real-world data is sometimes expensive to collect, or simply hard to come by. If you take for instance self-driving vehicles, the development of software for autonomous ... Read More