Datameer Blog

Introduction If you’re going to do machine learning work right, you’re going to need well-honed data sets to build your models on.  It is not just about cleaning up the data.  It is also about discovering…

In this blog, we cover five best practices for system administrators to keep users satisfied when it comes to maintenance updates: schedule, think holistically, review urgency, test changes incrementally and repeat changes into production.

In today’s fast-paced world, organizations must constantly adapt and innovate to maintain their competitive advantage. Cloud computing has revolutionized the technological landscape, allowing companies to “rent” time on online services without having rapidly-obsolescing hardware on-site.

Componentization, containers and the cloud have all converged to usher in a new era focused on “Ops.” It started with DevOps, which according to Wikipedia is defined as:

Last week we looked at The Ever Evolving Regulatory Environment and the need for a regulatory compliance architecture. If you didn’t see the first blog post on the topic, read it here.

Guest post by Philip Gilligan, Sand Hill East LLP

We have seen an extraordinary array of regulations in the last 8 to 10 years, globally as well as specifically in the US and EU. Starting with the US Dodd Frank Act during the great recession, it continued in Europe with a series of regulations, most recently around data privacy and protection concerns in the form of GDPR.

Last week we looked at how the healthcare industry (and vendors) would enjoy financial advantages of using Artificial Intelligence (AI), computer vision, IoT and more.

The healthcare industry is expected to undergo tremendous change and growth due to the overwhelming amount of data available today to help organizations make better, more informed and timely decisions. Patients and medical practitioners are poised to reap the benefits of safer, higher quality care offered through Artificial Intelligence (AI), computer vision (the AI strategy underpinning imaging and video analytics), IoT and more. At the same time, vendors, developers and healthcare organizations will also enjoy the financial advantages of using these technologies.

It feels like 1999 all over again, when Y2K was looming and IT pros were pulling consecutive all-nighters to get ready for it. GDPR, which is a set of rules under which the EU strengthens data protection for approximately 750 million people, is more than cleaning email lists and landing pages.

Last week we looked at industry trends that have contributed to the creation of market demand for public cloud solutions, what’s in the cloud analytics stack and Amazon integration pairs. If you missed it, check out part one first.

Today’s leading cloud platforms include numerous components for storing, processing and analyzing large volumes of data.  All the basics are there: storage, analysis and processing, streaming data processing, data pipelining, data warehousing, BI and even AI. But while it’s great to have all those raw components, how do you tie them together into a comprehensive architecture? While the parts are great, they still must be assembled into the whole.

While IDC forecasts tremendous payback from cloud investments and spending is estimated to grow at more than six times (17%) the rate of general IT spending (4%) through 2020, adoption forecasts are a little less clear — McKinsey reports that it hovers around 20 percent. Suffice it to say enterprises are taking their time, and for good reason, but it also means they’re stuck with environments and processes that are less than efficient until they adequately plan and execute their cloud transformation. It also means they’re giving the competition an advantage and risking higher support costs when business units go out on their own and buy cloud services.