CCPA took effect on Jan. 1, 2020, following the May 25, 2018, launch of the landmark global compliance regulation GDPR. When California begins enforcing CCPA on July 1, 2020, any for-profit entity doing business in California that collects, shares, or sells California consumers' personal data will be governed by CCPA.
Posted June 29, 2020
The CCPA deadline has come and gone. And, while the California attorney general won't enforce the act until July 1, just 5 months before its effective date, a recent survey revealed that only slightly more than one in 10 business owners and executives were aware of whether the law even applied to their business. Alarmingly, almost half had never heard of the regulation.
Posted June 26, 2020
In a world ruled by data, it is frightening to think how few people take protecting their information seriously. While it has become easy to share everything from an email address and mobile number to more sensitive personal information, what are the consequences of not safeguarding data?
Posted June 24, 2020
IT teams face an uphill battle in managing the deluge of apps that now populate enterprise networks. A big reason for this is that employees have access to a wide array of SaaS and cloud-delivered platforms—both business-critical tools and otherwise—that they can deploy in just a few clicks. This puts the onus on network teams to lay out specific policies about what kind of tools they'll allow on the network, as apps that could pose a threat to network performance are now increasingly common and easier than ever to deploy.
Posted June 23, 2020
Cybersecurity attacks have been increasing at an exponential rate. In 2018 alone, more than 2,000 data breaches were reported. The impact of these attacks has been calculated at more than $6 trillion. Given these statistics, the security of data lakes is of paramount importance. We all understand the value of a cloud data lake.
Posted June 22, 2020
The message on the business landscape is clear: Vulnerabilities are everywhere. They're in software, in hardware, in processes, and even in people. It only takes a small, unguarded threat vector for hackers to attack, invade, steal data, and wreck reputations.
Posted June 19, 2020
Dark data is a hot topic in the field of data management. Many perceive it as scary and aren't sure where to start in making it something of value. To back up, dark data is defined as data collected during business operations that otherwise goes unused. This unmanaged content is difficult to monitor, meaning it's hard to notice when information has been replicated, leaked, tampered with, lost, or stolen. It's easy to understand the ominous nature of the discussion around it.
Posted June 18, 2020
Alation, provider of data catalog software, is partnering with Databricks, provider of a unified analytics platform for data and AI, to help accelerate data science-led innovations. As data teams move to the cloud the new collaboration helps organizations to identify and prioritize mission-critical data for migration and diminish storage redundancies.
Posted June 17, 2020
According to Accenture's ninth annual Cost of Cybercrime study, the number of cyberattacks continues to rise and take more time to resolve. Organizations participating in the study saw an average of 145 attacks in 2018, up from 130 in 2017. The good news in the report was that prioritizing technologies to improve cybersecurity protection can reduce the consequences of attacks and "unlock future economic value as higher levels of trust encourage more business from customers."
Posted June 17, 2020
DBAs have always been central to how organizations manage, store, and use data. First, they were gatekeepers, limiting access to production environments and carefully shepherding database changes through to avoid the risk of data loss or system downtime.
Posted June 16, 2020
Data security is one of the most persistent issues facing federal, state, and local governments as well as commercial enterprises today, and often is one of the most alarming.
Posted June 15, 2020
Today, whether it is company leaders dealing with customer and business concerns or public health experts talking about the COVID-19 pandemic, what you hear again and again is that they are relying heavily on data. And, in this issue we look at the range of data management challenges and opportunities.
Posted May 28, 2020
Powering the next generation of renewable energy with IoT positively impacts running costs, while ensuring that wind power will continue to be both a viable economic solution for energy production for the future and a benefit to the environment.
Posted May 28, 2020
The pandemic is revealing gaps in our critical infrastructure security, supply chain fragility, and utilization of modern technologies to mitigate and recover communities globally. Although advanced technology platforms have been used by large international corporations, the pandemic is exposing the fact that emergency management and public health agencies are behind the curve or underutilizing data science, open source software, and high-performance computing resources.
Posted May 28, 2020
As companies have evolved toward digital business models and undertaken digital transformation initiatives, they have increasingly faced two challenges. First, the data they need to drive their real-time business processes is typically spread across multiple, siloed datastores. Second, their existing applications often cannot scale to address the increase in end-user demands for real-time engagement.
Posted May 28, 2020
A combination of factors is heightening the need for high-quality, well-governed data. These include the need for trustworthy data to support AI and machine learning initiatives, new data privacy and data management regulations, and the appreciation of good data as the fuel for better decision making.
Posted May 28, 2020
For several years, AI has been the enfant terrible of the business world, viewed as a technology full of unconventional and controversial behavior that has shocked, provoked, and enchanted audiences worldwide. That's all going to change. In 2020, AI will grow up, encountering new demands in the areas of responsibility, advocacy, and regulation
Posted May 28, 2020
Even the most ambitious data analytics initiatives tend to get buried by the 80/20 rule—with data analysts or scientists only able to devote 20% of their time to actual business analysis, while the rest is spent simply finding, cleansing, and organizing data. This is unsustainable, as the pressure to deliver insights in a rapid manner is increasing.
Posted May 21, 2020
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