Category Archive

Technology

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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.

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The nominations are in and – Who are we kidding? The results aren’t even close. The winner of Big Data’s Person of the Year is…The Chief Data Officer (CDO). Clearly congratulations are in order! But let’s step back for a second and take a look at the marketplace that’s made this all possible.

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Big data is really “the little engine that could.” While this may seem like an oxymoron, allow me to explain. When broken down, big data is really just a collection of seemingly infinite small details and information points in different silos. But all of these data points are really part of a much greater puzzle that, once “solved” and articulated, has the power to fuel digital transformation.

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2017 has been a big year for big data industry trends and for the Datameer team as well. From our introduction of SmartAI, which allows you to deploy artificial intelligence directly to your data lake, to our major announcement of Datameer Visual Explorer’s interactive data exploration capabilities, we’ve claimed our place among the movers and shakers of the 2017 Big Data Marketplace.

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Vivint Smart Home’s Miki Seltzer, data scientist, and Raul Olvera, senior data engineer, visited theCUBE, SiliconANGLE’s mobile livestreaming studio, and spoke with host Jeff Frick (@JeffFrick) They discussed how the company handles the massive amount of homeowner data it collects, Datameer Inc.’s role in analytics, and the future use of personal information by customers. View the complete interview here.

3 Steps to Optimize your Data Lake

Data today is quickly growing in volume, variability and complexity. This has left organizations with the challenge of harnessing all this data – however broad in variety or large in volume – to derive more value and insights from it.

Six Key Characteristics of a “Cloud-native” Platform

With the Cloud platform software market expected to reach $90 billion by 2020, even the largest and most conservative organizations are moving some or all of their analytics to the Cloud. According to the Gartner 2017 Magic Quadrant Business Intelligence and Analytics Platforms report:

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The cloud computing revolution has changed technology, and how businesses use it. It’s made for unprecedented levels of agility and flexibility in the use of, and budgeting for, technology. It’s lowered barriers to entry, it’s leveled the proverbial playing field and it’s also pressured organizations to accelerate their adoption of technology in order to stay competitive. But you knew all that.

Data Exploration vs. Data Discovery

Much has been made of the term “data discovery.” It is used profusely in the BI market and describes a fundamental transition in BI tools as emphasis has shifted from reporting to looking for new trends. Companies such as Tableau and Qlik altered the BI landscape with their ability to help business analysts discover new trends hidden in data.

Data Pipeline Optimization : Why Self-Sufficiency Accelerates Insight

The modern data pipeline has become an invaluable asset for many companies, allowing them to make well-reasoned business decisions fueled by the most up-to-date data possible. However, in today’s competitive business environment, collecting and compiling data is simply not enough to remain relevant. Proactive companies now strive to be “data driven” across many functions of the organization, using vast quantities of data, gathered from a plethora of sources that help to better define their business goals and company operations.

Datameer Visual Explorer: This Changes Everything

Datameer has introduced its new Visual Explorer component, and in my opinion, big data analysis has undergone a sea change because of it. I know that sounds hyperbolic, especially since I am not a disinterested party – but I am in earnest. Visual Explorer is a combination of technological breakthrough and a unique user experience that changes the landscape for doing exploration work with raw data at high-volume. In this post, I’d like to expound on why it’s so fundamentally transformational.

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At the heart of digital transformation is the creation of new data assets that drive the processes that fuel digital business. Optimizing and operationalizing the data asset creation process is at the core of the next iteration of the data lake, in which the data lake becomes the production line for the digital business. Companies that succeed at optimizing these production lines will ultimately have a tremendous leg up over their competition in the digital economy.