As companies shop for a cloud-based solution, it's critical to understand that there are some major differences in business practices among cloud software vendors. Some of these practices could have deep impact on the company's overall business operations—costing more time, money, and resources in the end.
Posted May 19, 2020
It is a matter of when, not if, your organization will confront a never-before-seen data source—a source that, if managed improperly, could result in catastrophic consequences to your brand and bottom line. In some cases, that data will be imported from outside your four walls. In others, the data will spring from new business processes or the fertile minds of your employees manipulating existing assets to create altogether new analytic insights,
Posted May 19, 2020
As data sizes have grown over the last decade, so has the amount of time it takes to run ETL processes to support the myriad downstream workloads. A decade ago, most people were only thinking about making their KPI dashboards faster. As time rolled forward, they started to think about getting more intelligent analytics out of their data, and the data sizes quickly grew from gigabytes to terabytes.
Posted May 18, 2020
With a multi-cloud strategy, businesses are finding that they can gain scalability, resiliency, and significant economic savings. However, this approach requires businesses to transition their architecture to a much more complex and decentralized model, which makes managing the security of the entire environment extremely challenging.
Posted April 09, 2020
The amount of data needed for real-time, customer-facing applications is impossible to operationalize when managed through software alone, according to Prasanna Sundararajan, CEO and co-founder of rENIAC.
Posted March 30, 2020
The Ethical Use of Artificial Intelligence Act was recently introduced by U.S. Senators Cory Booker (D-NJ) and Jeff Merkley (D-OR) with the goal of establishing a 13-member Congressional Commission that will ensure facial recognition does not produce bias or inaccurate results. Recently, Suraj Amonkar of Fractal Analytics, an AI and analytics company, shared his views on the proposed legislation and the issues it addresses.
Posted March 27, 2020
Competition these days is no longer just about cost or quality; it is about companies offering entirely new digital business models and better customer experiences that are based on insights. How do organizations compete on that basis? They do it by unlocking the various data sources that are imprisoned within IT and business departments, systems, and databases.
Posted March 24, 2020
Pandemics Happen—AI and Machine Learning Can Provide the Cures
Posted March 20, 2020
To democratize data and analytics is to make them available to everyone. It is an admirable goal and one with its roots in the earliest days of the self-service movement. If an organization is to truly be data-driven, it follows that all key decisions—from tactical operational priorities to strategic vision—must be data-informed. So where is democratization going wrong?
Posted March 20, 2020
GPUs fuel AI and machine learning. Initially created for video games, they are used in sports and business analysis by fantasy baseball enthusiasts, oddsmakers, and front office executives who want to enhance their understanding of the hidden value of often obscure players. Other uses of this technology's extreme processing power include the recognition of animals, such as dog breeds or endangered species, to allow biologists to gain a more accurate understanding of species populations in a geographical area.
Posted March 17, 2020
As more and more organizations migrate database management and integration to the cloud, various use cases and best practices are beginning to take shape around the timing, cost, and extent to which workloads are moved.
Posted March 17, 2020
Quantum computing continues to captivate imaginations. The technology takes advantage of quantum mechanics to deliver exponentially faster speeds by being able to process an almost infinite amount of parallel compute threads delivered as qubits and quantum gates. As Jim Clarke, director of quantum hardware for Intel Labs, describes it, "by harnessing quantum mechanics, quantum computing systems promise an unprecedented ability to simulate and analyze natural phenomena, significantly accelerating the ability to process information and answer questions that would require prohibitive amounts of time even for today's supercomputers."
Posted March 17, 2020
There's no question that investing in data systems and infrastructure can make organizations more competitive and allow for new, exciting innovations. This makes every company a data company. But recently, the maxim has come into sharper focus. The big competitive advantage doesn't come from data-at-rest; instead, it comes from streaming data.
Posted March 16, 2020
Improving Database Change: Q&A with Datical's Dion Cornett
Posted March 04, 2020
AI is capturing attention as a transformative technology for enterprises. Fundamental to AI is the use of ontologies, says Seth Earley, CEO of Earley Information Science (EIS), a consulting firm focused on organizing information for business impact. His new book "The AI Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster and More Profitable," due out in April, focuses on the importance of ontologies as a foundation for AI success.
Posted March 02, 2020
data.world, the cloud-native data catalog company, has expanded its partnership with Snowflake, the cloud data platform, that includes integration to Snowflake Partner Connect.
Posted February 13, 2020
Red Hat OpenShift Container Platform is generally available for IBM Z and IBM LinuxONE, reinforcing the agile cloud-native world of containers and Kubernetes with the security features, scalability, and reliability of IBM's enterprise servers.
Posted February 13, 2020
Dun & Bradstreet, a provider of business decisioning data and analytics, is releasing the D&B Analytics Studio. The platform is a secure, cloud-based analytics platform that will provide clients with a single, integrated solution to explore, synthesize, and operationalize data and analytics in order to remain competitive in the era of digital transformation.
Posted February 12, 2020
The Evolving Cloud Picture: Q&A with Steve Daheb, Senior Vice President, Oracle Cloud
Posted February 11, 2020
How CEOs Can Navigate the Muddying Waters of Data Privacy Regulation
Posted December 30, 2019
Making It Measurable—Justifying Investments in Data and Data Quality for AI and Machine Learning
Posted December 30, 2019
Opportunity and Threat: The Intersection of AI and Data Governance
Posted December 23, 2019
How AI Strengthens Enterprise Data and Analytics Programs
Posted December 23, 2019
The Age of the Contextualist
Posted December 16, 2019
Accelerating the Data Science Ecosystem
Posted December 16, 2019
DBMS 2020: State of Play
Posted December 09, 2019
Hybrid Clouds—Myth or Reality?
Posted December 09, 2019
Solving CPU Bottlenecks in a Mobile-First World
Posted December 02, 2019
The Role of ETL and Data Prep in the Cloud
Posted December 02, 2019
A Road Map to Closing the Data Science Skills Gap
Posted December 02, 2019
Hewlett Packard Enterprise has announced the HPE Container Platform, an enterprise-grade Kubernetes-based container platform designed for both cloud-native applications and monolithic applications with persistent storage. With the HPE Container Platform, the company says, enterprise customers can accelerate application development for new and existing apps—running on bare-metal or virtualized infrastructure, on any public cloud, and at the edge.
Posted November 18, 2019
PlanetScale has announced the general availability of PlanetScale CNDb, a fully managed cloud native database designed on Vitess, a Cloud Native Computing Foundation (CNCF)-hosted open source project that serves massive scale production traffic at large web-scale companies such as YouTube, Slack, and Square.
Posted November 18, 2019
Just as in the oil industry, exploitation of data comes down to how good your refinery capabilities are. Just as oil has to be refined to get valuable products out of it, such as gasoline and jet fuel, data has to be refined into insights. And, just as in the old days of the oil business, the rush is on.
Posted September 26, 2019
There is no substitute for genius, and despite the awesome power of the GPU and the majesty of the new manifestations of AI, there is no substitute for the human mind.
Posted September 26, 2019
As business analytics education, including specific instruction in data visualization, becomes more solidified in higher education, the question is not: "Are we teaching business analytics?" but instead becomes: "What are we teaching in business analytics?" To make education most valuable, it should align with what the market is looking for in potential job candidates.
Posted September 26, 2019
While on the surface Wall Street may appear conservative and risk-averse, when it comes to IT, the financial services industry has continually led the adoption of new technologies—sometimes out of a drive for innovation, and other times out of necessity.
Posted September 26, 2019
IT executives and line-of-business experts understand the importance of data for their success and are adopting modern technologies to enable the delivery of timely data and insights to enhance decision making. In line with their data-driven goals, organizations are leveraging hybrid and multi-cloud strategies. However, they are also finding that cloud approaches add their own complexity.
Posted September 26, 2019
It might be the most frequently asked question of a data governance consultant: "Who should own data governance, the business or IT?" And man, that's a loaded question! When you dig deeper into the root of the question, most people really want to know one of two things—"Who should ultimately own data decision making for our company?" or, "Where will data governance be most successful?" Let's take a closer look at those two questions.
Posted September 26, 2019
Multi-cloud offers many benefits—in terms of documented security, compliance, and savings outcomes—but every migration presents challenges. Understanding best practices around how to successfully launch a multi-cloud migration journey is crucial to avoiding the common pitfalls along the way.
Posted September 26, 2019
Has the meaning of big data changed? Many agree that data no longer has to be "big" to meet today's evolving requirements. In particular, open source and cloud tools and platforms have brought data-driven sensibilities into organizations that previously did not have such expertise, making big data more accessible.
Posted September 26, 2019
Big Data 50—Companies Driving Innovation in 2019
Posted September 11, 2019
It is well-known that data scientists spend about 90% of their time performing data logistics-related tasks. Anything that a data scientist can do to reduce it is a good use of their time, and a benefit to the organization as a whole. Enter RAPIDS—a data science framework offering support for executing an end-to-end data science pipeline entirely on the GPU.
Posted September 03, 2019
Databricks, a provider of unified analytics and original creators of Apache Spark, is boosting its Unified Analytics Platform with automation and augmentation throughout the machine learning lifecycle.
Posted August 20, 2019
Stardog, a provider of Enterprise Knowledge Graph technology, is releasing Stardog 7, including a new storage engine that is dramatically faster, providing between 10x and 20x improvement for write performance.
Posted August 14, 2019
Start-up Trinity Cyber is closing on $23 million in funding from top institutional investors led by Intel Capital, allowing the company to further invest in preventing cyberattacks.
Posted August 13, 2019
Lucidworks, a provider of AI-powered search solutions, announced a $100 million funding round from investors, including Francisco Partners, a global technology-focused private equity fund, and TPG Sixth Street Partners, a global finance and investment firm. With the investment, Francisco Partners and TPG Sixth Street Partners join Top Tier Capital Partners, Shasta Ventures, Granite Ventures, and Allegis Cyber.
Posted August 12, 2019
The Cloud Security Alliance(CSA) has released a list of the top threats to cloud computing which it has dubbed "The Egregious Eleven."
Posted August 12, 2019
Perspective on Data Governance: Q&A with Myke Lyons, Chief Information Security Officer at Collibra
Posted August 07, 2019
HPE Acquires Business Assets of MapR
Posted August 06, 2019
As the 2.0 release was rolled out in July, Dipti Borkar, VP, product management and marketing at Alluxio, reflected on the data engineering problems that have emerged as a result of the increasingly decoupled architecture for modern workloads. Just as compute and containers need Kubernetes for container orchestration, Alluxio contends, data also needs orchestration—a tier that brings data locality, accessibility, and elasticity to compute across data silos, zones, regions, and clouds.
Posted July 30, 2019