Big Data News – 22 Jul 2016

Today's Infographic Link: UFO Sightings

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The concept of big data isn't new at all. While the exact conception point of modern big data can likely be traced back (according to Forbes) to the identification of the "information explosion" back in 1941, what has changed recently isn't just the volume, variety, and velocity of data — but rather the tools that we have to store and analyze the data. Certainly, volume, variety, and velocity are growing more today, as well, since the bulk of big data is produced by machines, not humans.

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Most surveyed organizations revealed their data is not highly integrated as it moves throughout key customer channels such as the Web, smartphones and mobile devices.

Fast-growing Hudl provides coaches and athletes with key feedback based on its customers' video uploaded to the cloud. Like many other startups, the company relies on Amazon Web Services for its backend support.

Chris Wilson, former Director of Data and Analytics for Ted Cruz for President, explains the role of big data in the 2016 presidential campaign and how every business can use direct targeting to reach customers.

Springboard just published an online guide to data science interviews, "Ultimate Guide to Data Science Interviews" that covers everything from the job hunt to accepting an offer!

At scale, Microsoft is likely the only company offering a cloud solution that is robust enough to be trusted in an incredibly unsafe world.

The 'as-a-service' market now accounts for a third of IT services activity. Can traditional outsourcing survive?

Machine learning, cloud services, and artificial intelligence-enabled human agents are all combining to change the way that companies can order services, buy goods, and even hire employees and contractors.

Developers interested in creating apps that understand text or speech can look to Google's cloud for tools — Cloud Natural Language API and Cloud Speech API. The two offerings have now advanced into open beta status.

The three reasons that departments' own adoption of cloud technologies benefits CIOs' goals

Keeping pace with advancements in software delivery processes and tooling is taxing even for the most proficient organizations. Point tools, platforms, open source and the increasing adoption of private and public cloud services requires strong engineering rigor — all in the face of developer demands to use the tools of choice.

There will be new vendors providing applications, middleware, and connected devices to support the thriving IoT ecosystem. This essentially means that electronic device manufacturers will also be in the software business. Many will be new to building embedded software or robust software.

With the proliferation of both SQL and NoSQL databases, organizations can now target specific fit-for-purpose database tools for their different application needs regarding scalability, ease of use, ACID support, etc. Platform as a Service offerings make this even easier now, enabling developers to roll out their own database infrastructure in minutes with minimal management overhead. However, this same amount of flexibility also comes with the challenges of picking the right tool, on the right provider and with the proper expectations.

Find out what Tableau is.

After several months of hard work, we are proud to unveil our web site with a new look and feel!  We hope you like it! Though you may have already seen it through our site, we now have completely migrated all user information (including information about completion certificates previously earned), and we now have enabled final exams and badges.

"When you think about the data center today, there's constant evolution, The evolution of the data center and the needs of the consumer of technology change, and they change constantly," stated Matt Kalmenson, VP of Sales, Service and Cloud Providers at Veeam Software, in this interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY. has signed a definite agreement to acquire Coolan, the developer of a platform for data center hardware analysis and optimization. The acquisition appears to be designed to help Salesforce boost its own infrastructure for its customer relationship management software. "Once the transaction has closed, the Coolan team will help Salesforce optimize its infrastructure as it scales to support customer growth around the world," Amir Michael, Coolan's cofounder and CEO wrote in a blog post on Thursday. A Salesforce spokeswoman confirmed the acquisition. Financial terms of the deal were not disclosed.

While the pace of venture capital investment in technology startups declined during the first half of this year, some analytics and database companies are reporting continuing and expanding investments. Among them is Redis Labs Inc., which this week disclosed a $14 million funding round at what it claimed was a "significantly increased valuation."

We all know the latest numbers: Gartner, Inc. forecasts that 6.4 billion connected things will be in use worldwide in 2016, up 30 percent from last year, and will reach 20.8 billion by 2020. We're rapidly approaching a data production of 40 zettabytes a day — more than we can every physically store, and exabytes and yottabytes are just around the corner.

Venafi has extended the power of its platform in an easy-to-use utility for DevOps teams available for immediate download. Now DevOps teams can eliminate the hassle of acquiring and installing TLS keys and certificates. Instead, customers can focus on speeding up continuous development and deployment, while security teams have complete visibility and can keep the DevOps environment secure and compliant to protect customer data.

Magnitogorsk Iron and Steel Works (MMK), Russia's third largest steel works, is to save more than £3 million in steelmaking costs by using a machine learning and big data analytics service from Yandex Data Factory.

SYS-CON Events announced today that Venafi, the Immune System for the Internet™ and the leading provider of Next Generation Trust Protection, will exhibit at @DevOpsSummit at 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Venafi is the Immune System for the Internet™ that protects the foundation of all cybersecurity — cryptographic keys and digital certificates — so they can't be misused by bad guys in attacks.

Networking IoT devices will be a massive undertaking, and there is room for more than one approach.

SQL-on-Hadoop query engines are becoming a common companion of Hadoop in big data systems as IT managers look to ease programming for analytics applications and data integration jobs.

As the Big Data marketplace moves closer to a point of mass-maturity, business leaders have begun to take new approaches to implementation and utilization. Advanced analytics solutions have made their way into a range of industries and regions, and companies that successfully align these investments with core goals and requirements will enjoy more progressive improvements to operational sustainability, intelligence and general performance. However, there is some housekeeping that must be addressed as organizations embark on Big Data and analytics initiatives.

Apache Spark has become the defacto standard computational engine in the big data world. But as an in-memory technology, Spark has limitations. One of the ways people are getting around those limitations is by pairing Spark with superfast, Flash-based NoSQL databases, including key-value stores. Big data architects have an abundance of technologies to work with at the moment, including Apache Spark, the computational Swiss Army knife that has quickly replaced MapReduce as the core data processing engine in Hadoop.

You think you know what's in your data. But do you? Most organizations are now aware of the business intelligence represented by their data. Data science stands to take this to a level you never thought of — literally. The techniques of data science, when used with the capabilities of Big Data technologies, can make connections you had not yet imagined, helping you discover new insights and ask new questions of your data.

Whether your mission is to improve external collaboration, increase scalability or focus on security and compliance, find out how content collaboration with Box can improve your ROI.

To ensure data science success, you need to provide data scientists with an environment that is open, engaging, and fosters collaboration. To explore how your data scientists can access all the open functionality and expertise they'll need for critical projects, join the new Data Science Experience.

Contrary to popular opinion, there are new reports about overall security issues with iPhones and iOSs.

Editor's note: Welcome to Throwback Thursdays! Every third Thursday of the month, we feature a classic post from the earlier days of our company, gently updated as appropriate. We still find them helpful, and we think you will, too! The original version of this post can be found here. This is a great time for big data in business. There's a widespread awareness of the value of big data analytics, and plenty of use cases that demonstrate its potential: understand your customer, optimize your supply chain, provide personalized app and media experiences.

Introduction This two part blog is based on my forthcoming book:  Data Science for Internet of Things. It is also the basis for the course I teach  Data Science for Internet of Things Course.  I will be syndicating sections of the book on the Data Science Central blog.  Welcome your comments.  Please email me at ajit.jaokar at  – Email me also for a pdf version if you are interested in joining the course  

In the first post in this two-part series, I summarized the journey to Hadoop at Dell SecureWorks. In this follow-on post, I will wrap up the story of our Hadoop journey with a look at five key lessons that we learned. Keep these important best practices in mind should you embark on your own Hadoop journey. Lesson 1: Start with the end in mind Our Hadoop journey began with this goal: getting all data flowing into our proprietary system to also flow into our Hadoop cluster.

  Join us for this one hour webinar to learn how your enterprise can do more with Hadoop and Spark. Data continues to grow at an exponential rate. With this reality, organizations are racing to better understand every piece of data to optimize and grow their businesses. Capabilities provided through Hadoop and Spark are key to maximizing the potential of your Data. In this session we will provide a detailed introduction to both Hadoop and Spark to learn and explore how these capabilities co-exist for exceptional analytics. We will discuss five use cases that will provide real world example.

Microsoft has a brand-new conference, exclusively for data scientists, big data engineers, and machine learning practitioners. The Microsoft Data Science Summit, to be held in Atlanta GA, September 26-27, will feature talks and lab sessions from Microsoft engineers and thought leaders on using data science techniques and Microsoft technology, applied to real-world problems. Included in the agenda are several topics of direct interest to R users, including: The Data Science Virtual Machine, which includes R Deploying Predictive Maintenance solutions with Cortana Intelligence Using the Cognitive Services framework, which you can use to incorporate machine intelligence into R scripts Other topics of interest include building with bot frameworks, deep learning, Internet of Things applications, and in-depth Data Science topics.

Microsoft has a brand-new conference, exclusively for data scientists, big data engineers, and machine learning practitioners. The Microsoft Data Science Summit, to be held in Atlanta GA, September…

Virtual digital assistants will have a profound effect on the cost of delivering online customer service.

Open doors to data science with a multidisciplinary master's degree from the University of Wisconsin!  Hello aspiring Data Scientist, According to a recent survey, 88% of data scientists have a master's degree. Are you keeping up with the field? Data Science is a broad industry with opportunity in multiple disciplines.

As Azure SQL Data Warehouse reaches general availability, it brings massively parallel processing to a wider audience, and augers more competition in the cloud data space.

Businesses see AI as a future investment, even though most organizations are actually already using it, a study finds.

The next BriefingsDirect security market transformation discussion focuses on the implications of the European Parliament's recent approval of the General Data Protection Regulation or GDPR. This sweeping April 2016 law establishes a fundamental right to personal data protection for European Union (EU) citizens. It gives enterprises that hold personal data on any of these people just two years to reach privacy compliance — or face stiff financial penalties. But while organizations must work quickly to comply with GDPR, the strategic benefits of doing so could stretch far beyond data-privacy issues alone.

Introduction Imagine you own a popular mobile health app, with millions of users worldwide, that continuously records new information. It sends over one million updates per second to its master data store and needs the updates to be relayed to various replicas across different regions in real time. Amazon DynamoDB and DynamoDB Streams are accustomed to operating at this scale; and, they can handle the data storage and the updates capture for you. Developing a stream consumer application to replicate the captured updates to different regions at this scale may seem like a daunting task.

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