Above the Trend Line: machine learning industry rumor central, is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz. Our intent is to provide our readers a one-stop source of late-breaking news to help keep you abreast of this fast-paced ecosystem. We’re working hard on your behalf with our extensive vendor network to give you all the latest happenings. Heard of something yourself? Tell us! Just e-mail me at: daniel
We’re closing in on the end of a very busy year for big data, but the pace over here at insideBIGDATA continues at a frenetic level. We have a number of juicy tidbits this week starting with new funding news: ZEPL announced $4.1million in Series A funding, with a fresh new brand. Formerly known as NFLabs, ZEPL is the company founded by the creators of Apache Zeppelin. With this new funding, the company plans to continue to disrupt the enterprise analytics space. The round was led by Vertex Ventures, with participation from Translink Capital, Specialized Types, and Big Basin Capital. With the funding, In Sik Rhee, General Partner at Vertex Ventures, joins the company’s board. Apache Zeppelin breaks down walls by providing a beautiful, pluggable, open source solution. With Zeppelin, data engineers, data scientists, and business analysts can all use and share the same interface to source, process, and analyze all data types. Apache Zeppelin supports most modern day frameworks—from Spark, Cassandra, MongoDB, Elastic Search—as well as standard relational databases (Oracle, MySQL) with its JDBC interpreter … SnapLogic , announced $40 million in Series F funding to accelerate global expansion and dramatically transform how companies integrate data, applications and devices for digital business. The new round was led by European private equity firm Vitruvian Partners, with follow-on investment from Andreessen Horowitz, Capital One, Ignition Partners, NextEquity Partners and Triangle Peak Partners. SnapLogic has raised a total of $136.3 million to date. SnapLogic uses its cloud-based platform to “snap” together cloud and on-premise applications, data warehouses, big data streams and IoT deployments. Unlike traditional integration software that requires painstaking, hand-crafted work by teams of developers, SnapLogic makes it fast and easy to create data pipelines with no coding. Analysts, data scientists and business users can now create integrations in hours rather than weeks, using visual drag-and-drop software. Under the hood, SnapLogic’s powerful data streaming architecture delivers real-time processing with high throughput to get the right data to the right people at the right time.
We also heard of a number of new partnerships, alignments and collaborations starting with Ryft, a leader in fast, simple heterogeneous compute solutions, announcing it has partnered with Amazon Web Services to deliver the speed and simplicity of the Ryft ONE to AWS’ F1 customers. Ryft Virtual, a heterogeneous cloud-based version of its core Ryft ONE technology, enables AWS users to get fast, actionable insight from their data at an order of magnitude faster than is possible with current CPU-based infrastructures. With the AWS F1 instance, all organizations can now use the power of heterogeneous computing, and with Ryft Virtual, they get not only the speed but also the incredible ease of use of the Ryft ONE. Amazon’s announcement of the new offering comes at a time when organizations are finally coming to grips with the fact that businesses must embrace heterogeneous computing to solve the problems that today’s fast and varied data create. But when FPGAs are difficult for the average data scientist to understand — let alone use — just having an FPGA-based heterogeneous cloud is not enough. This is why Ryft has partnered with AWS not only to provide the supercharged analytics that companies require but also to deliver a Ryft Virtual application that is as simple as what they currently use … Azul Systems, a leader in Java runtime solutions, announced that it has partnered with Hazelcast, a leading open source in-memory data grid, to ensure explicit Service Level Agreement (SLA) assurance for Java-based in-memory computing applications. By combining Zing plus Hazelcast Enterprise, Java-based businesses are now able to deliver consistent in-memory application performance without the risk of performance-robbing Java runtime artifacts … Several West Coast companies – including Alteryx & Tableau – working with PATH, an international non-profit organization for global health innovation, are using advanced analytics/big data to wipe out malaria completely from Zambia by 2020. The partners have combined their data knowledge and capabilities to improve data accuracy and make critical data-driven decisions about how and where to tackle malaria outbreaks. For example, their models can predict where malaria is mostly likely to break out—and the government can use that information to make steps to prevent it from happening. The ultimate goal is for the successful (and repeatable) model to wipe out malaria, globally, for good.
In the customer wins department we heard that JUST Capital released it’s “JUST 100 List,” which ranks the publicly traded companies in America that perform best on the priorities of the American public. In order to manage the complex survey data and ensure that the list was as accurate as possible, JUST Capital partnered with GoodData. JUST Capital chose GoodData over other analytics platforms for its powerful back end capabilities, in combination with user ease in creating and orchestrating ETL processes. The GoodData services product team was instrumental in helping conceptualize and define the KPIs required to prove to the public that the companies listed in the JUST rankings are relevant and accurate. With their added expertise, the two companies were able to partner to determine the insights needed to not only measure, but more importantly, improve corporate JUSTness … Solution VOZIQ utilizes Lexalytics text analytics technology to process customer interactions and analyze consumer behaviors. Through their Semantria implementation, VOZIQ analyzes the text comments each contact center agent adds in their CRM systems at the end of phone calls. Semantria generates categories such as billing issues, product issues, service delays and even competition references or contract inquiries from everyday contact center interactions, providing key differentiation to VOZIQ’s predictive churn models. In addition, Semantria also identifies customer sentiment from survey scores and keywords in each call log. This information offers a window into the intention behind each call and customer motivations, helping VOZIQ drive a 2x faster reduction in customer churn for their clients. Since partnering with Lexalytics, VOZIQ has retained several thousand customers for their clients, resulting in millions of dollars in additional revenue each year.
In benchmark results we heard Cambridge Semantics, a leading provider of graph-based Smart Data management and exploratory analytic solutions, unveiled that its Anzo Graph Query Engine™ completed a load and query of one trillion triples as a Google Cloud Partner on the Google Cloud Platform in just under two hours, 100 times faster than the previous solution running the Lehigh University Benchmark (LUBM) at the same data scale. The LUBM is an industry standard that evaluates the query performance of semantic web repositories over a large data set. A ‘triple’ consists of a subject, predicate and an object. In the LUBM test conducted on the Google Cloud Platform on Oct. 31, 2016, Cambridge Semantics’ Anzo Graph Query Engine was able to load and query 1.065 trillion triples in 1.98 hours, surpassing the previous LUBM benchmark of 220 hours set by Oracle in September 2014. To place the data results in context, examples of one trillion triples includes:
- six months of worldwide Google searches
- 133 facts for each of the 7 billion people on earth
- 100 million facts describing all the details of each of 10,000 clinical trial studies
- 156 facts about each device connected to the internet
New financial results included – Interana, a leader in interactive behavioral analytics for digital businesses, announcing that it surpassed user and revenue goals for the eighth quarter in a row, reporting 135 percent year over year (YOY) growth in Annual Recurring Revenue (ARR). The company also announced new additions to its rapidly expanding customer roster including Microsoft Office, Bleacher Report, Comcast and Hootsuite, among others. With a recent infusion of fresh capital and a growing team of data industry veterans, Interana is poised to dominate the analytics market as digital transformation drives demand for interactive behavioral exploration.
We learned of a number of new products, services and solutions starting with ABBYY, a leading provider of technologies and solutions to action information, today announced the launch of the ABBYY.cloud platform that provides services and solutions in the cloud – capture and transfer of information from paper documents into business applications, accurate content classification and prompt translation in 80 languages. With ABBYY.cloud organizations can access a wide variety of tools for knowledge processing from a single dashboard. As the cloud market continues to accelerate in 2017 an increasing number of organizations are moving workloads to the cloud in a big way. According to Forrester’s Dave Bartoletti, enterprises need to take a fresh look at industry-specific cloud providers with specialization and get their cloud strategies in shape. ABBYY.cloud is designed to help such enterprises to process, digitize and extract data from a wide variety of sources including images, text and invoices. Furthermore, ABBYY.cloud customers can leverage both automated and professional human services from ABBYY … Dell Boomi (Boomi) announced the Fall 2016 release of its award-winning integration Platform as a Service (iPaaS) to help organizations rapidly and cost-effectively integrate data across applications in hybrid IT environments of cloud-based and legacy on-premises systems. The latest release enables Boomi customers to more efficiently build a connected business at scale, with new features to increase user productivity, accelerate implementation and provide unparalleled control of integrations.
In the M&A department, the big news this week was that Microsoft will acquire LinkedIn.
Microsoft’s acquisition of LinkedIn isn’t a social play, it’s a big data power-play. Microsoft CEO Satya Nadella has been known to say that data is the new currency for the enterprise. LinkedIn’s 400 million profiles comprise a vast and unique pool of data that is highly valuable to B2B organizations. Well-curated, relevant data has become do-or-die for enterprise software businesses and Microsoft has really thrown down the gauntlet with this news.” – Dave Elkington, CEO and founder, InsideSales.com
And finally, our Vendor of the Week is Alluvium, developers of Mesh Intelligence solutions that harness machine learning insights for real-time applications in industrial use cases. The company announced $2.5 million in seed funding led by investors IA Ventures, Lux Capital, and Bloomberg Beta. The machine learning venture is running pilot projects of its Mesh Intelligence technology in fleet management, and oil and gas, among other vertical industrial applications. Alluvium aims to conquer one of big data’s greatest unsolved challenges for complex industrial operations with expert human operators. Alluvium’s breakthrough Mesh Intelligence solution frees the data from these proprietary systems, transforms it into rich information streams, and provides real-time insights to human operators for immediate action. The company was founded by pioneer data scientist Drew Conway, who earned his PhD at NYU, and is a leading expert in the application of computational methods to social and behavioral problems at large-scale.
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