Click to learn more about author Cathy Nolan. Maybe we should ask, ?who or what killed anonymity?? The question being debated over and over again is ?have we given away our privacy for convenience and security?? It would appear that the answer is ?yes?. Some of our privacy we give away without even knowing it, but [?]
The evolution of analytics and machine learning are shaping the industry's future, mitigating risk, improving business, and helping develop types of policies that individuals and businesses need, even before they know they do.
Companies today face incredible challenges around compliance, security and analytics, as their data lakes fill with invaluable information from ever more sensors. And tomorrow?s challenges will be no easier. As the digital age expands to cover all facets of our lives, more and more computing power will be necessary to process all of the data created.
A good indication of whether a technology is in the plateau of productivity in Gartner?s hype cycle is when someone asks ?Is MongoDB dead?? on that bastion of, um, sane discussion, Quora. A second good indication is when there are productivity tools and at least a nascent third-party market around your technology. A third indication is when a third party creates an IDE for it: The growing third-party market is a key indication that MongoDB has moved from mere maturity to one of the dominant players in this market.
Click to learn more about author Chirag Shivalker. Customers are engaging with businesses through ever increasing touchpoints including websites, social media, in-store, mobile, and tablets. It?s really ironic that irrespective of how they engage with your company, they expect customized, personalized and consistent experience every time. These expectations have proved lethal for enterprises to fulfill, [?]
2017 was a memorable year for the tech industry?and not always in a good way. From the massive Equifax data breach to problems at Uber and the challenges with fake news on social media, technology was in the headlines more than I can ever remember.
The amount of new technologies in 2017 has been overwhelming: The cloud was adopted faster than analysts projected and brought several new tools with it; AI was introduced into just about all areas of our lives; IoT and edge computing emerged; and a slew of cloud-native technologies came into fruition, such as Kubernetes, serverless, and cloud databases, to name a few. I covered some of these a year ago in my 2017 predictions and it?s now time to analyze the trends and anticipate what will likely happen in the tech arena next year.
The IoT revolution is here. Connected devices are reaching every part of our lives, from wearables, to the smart home, to the industrial internet. (This infograph created by First Mark Capital does a great job of showing the breadth and reach of the internet of everything).
It's not surprising that men and women value different things in the workplace, but employers aren't necessarily paying attention to the details. Going into 2018, here are a few things you should know.
Big Data has been described by some Data Management pundits (with a bit of a snicker) as ?huge, overwhelming, and uncontrollable amounts of information.? In 1663, John Graunt dealt with ?overwhelming amounts of information? as well, while he studied the bubonic plague, which was currently ravaging Europe. Graunt used statistics and is credited with being [?]
Click to learn more about author Tripti Rai. With 4.77 billion mobile phone users right now, there?s no exaggeration in saying that mobile app development is the right place to invest in. Every brand is turning towards mobile apps to reach the wider audience, cater their needs, and enjoy higher ROI. However, it is not [?]
AWS Educate serves as a path for younger students to understand and get excited about the capabilities of the cloud, namely Amazon?s own AWS cloud. At AWS?s Re:Invent conference in last week, AWS announced the company is expanding its cloud education initiative to students ages 14-17.
2017 has been a pivotal year for the database technologies market, with several massive paradigm shifts that shows no signs of stopping anytime soon. Companies are pivoting away from the traditional monolithic database architectures which, for decades, powered generations after generations of applications in exchange for a more optimized, agile, self-managed cloud-focused data platform strategy.
With the amount of data in the world predicted to increase at least 50 fold between 2010 and 2020, how we store that data has come into sharp focus. Collecting large volumes of raw log data from multiple applications and infrastructure components and sending it to a central location for storage and processing, for example, increases the size and cost of storage. And as the volume of data grows and storage and processing costs increase dramatically, businesses risk undermining the advantages big data brings. Furthermore, the surging demand for data has environmental implications; by 2020, 12 percent of the world?s energy consumption will be taken by our digital ecosystem, and this is expected to grow annually at approximately 7 percent until 2030.
?The quality of service a company can deliver after the initial sale is important to the overall long-term financial health of the company, and Predictive Analytics can fundamentally improve the way a company can deliver service,? said Gary Brooks, Chief Marketing Officer at Syncron in a recent DATAVERSITY® interview. Syncron specializes in using Predictive Analytics [?]
In separate announcements, Microsoft Corp. and Daimler indicated that hydrogen fuel cells could provide significantly better energy solutions for data centers than existing electrical grid and backup power technology.
Building your brand online can be one of the most profitable activities you engage in. Although defined broadly, branding is basically about creating a consistent, catchy image and ideology that comes to define what your product and service line is all about. Branding is an important and ultimately inalienable component... Read more »
TensorFlow has emerged as one of the leading machine learning libraries, and when combined with an operational database, it provides the foundation for quickly building sophisticated machine learning workflows.