Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category 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 you a one-stop source of late-breaking news to help you keep 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
The boiling hot summer (at least here in Los Angeles) continues to bear down on us all, in a way similar to how HOT the big data industry is right now. Whew! So much technology, so little time. Let’s start our regular review with some new funding news … Redis Labs, the home of Redis and provider of Redis Enterprise, announced it has raised $44 million in Series D funding. This brings the company to $86 million in total funding to date. The round was led by new investor Goldman Sachs Private Capital Investing and existing investors Bain Capital Ventures and Carmel Ventures, with participation from Dell Technologies Capital … LevaData, the Cognitive Sourcing Platform provider that offers global enterprises the ability to improve gross margins by reducing supply chain costs, has announced a $5 million Series A investment from Tola Capital. This funding will enable LevaData to continue to invest in the only solution available today that focuses on improving sourcing and procurement decisions through artificial intelligence … Taiger, a Singapore-based company specialising in applied Artificial Intelligence (AI) solutions, has successfully closed its Series A round. The S$8 million funding was led by Tembusu ICT Fund I and included SGInnovate, in a boon to Singapore’s efforts to become a leader in AI. The funding comes from Tembusu ICT Fund I, the only software-focused venture capital fund in Singapore and one of the six funds selected by the National esearch Foundation of Singapore (NRF) as part of the Early Stage Venture Fund II scheme. SGInnovate, a government-owned entity which operates under the NRF, has also participated in this round … Elon Musk wants to connect your brain directly to a computer, and investors are ready to make that science fiction a reality. Musk’s startup Neuralink has raised the $26.96 million of a technically still-open funding round that could grow to $100 million, according to a new SEC filing. Few details are known about the startup—the company’s website says it’s “developing ultra-high bandwidth brain-machine interfaces to connect humans and computers.” It’s also recruiting engineers and scientists to join the effort, stating “no neuroscience experience is required: talent and drive matter far more.”
Pascal Kaufmann, Neuroscientist and Founder of Starmind gave us some interesting comments about the Neuralink funding. He believes much like Google’s AI powerhouse DeepMind, that we need to better understand the brain to get where Musk wants to go. Until we understand how the brain works (“cracking the brain code”)—we will not be able to achieve fully connecting computers and brains. However, if we put resources into understanding how the brain works, and apply the investment dollars here— we will have a better shot at truly connecting humans and computers— opening the door for True AI and life changing discoveries.
In new people movements news we heard … Stibo Systems, the global leader in Business-first Master Data Management (MDM)™ solutions, announced two executive appointments designed to help drive the company’s next phase in its ongoing mission of delivering superior business outcomes for customers. Prashant Bhatia joins the company as Chief Marketing Officer and Brad Crosby as President, North America (NA), replacing Andreas Lorenzen who is retiring after more than 30 years of exceptional service … MapD Technologies announced the expansion of its leadership team to seize the market potential of GPU-powered analytics. Justin Sears joins MapD as VP of Product Marketing, Ashish Sahu becomes VP of Product Management, and Ashish Bambroo takes up the position of VP of Business Development. The hires come as MapD gains traction having recently signed deals with Huawei, Harvard CGA and Tutela, and on the heels of the VP-level appointment of Aaron Williams to lead the company’s open source community efforts … Teralytics, a venture-backed big data, machine learning location analytics specialist headquartered in Zürich, has appointed Robin Williamson as its new Vice President of Engineering. Robin’s career began at IBM and he went on to hold executive roles in American software startups. Most recently, he spent 10 years as an Engineering Director at Google’s Research and Development Center in Zürich. As Vice President of Engineering, Robin will be responsible for leading the Teralytics engineering team and helping them deliver exceptional, previously unattainable insights around the movement of people and populations to the company’s clients. Robin intends to transform the speed, scalability and client focus within the engineering team by improving the way Teralytics approaches its data architecture, elevating stratospheric internal standards to even higher levels, and by maintaining a balance of world class delivery in the here and now with the pre-existing culture of cutting edge innovation around data science and machine learning applied to rare and sensitive data.
Financial results for the period include … Conversica, a leader in conversational AI for business, announced a record-breaking first half of the company’s fiscal year, with accelerated growth in bookings and revenue, major new capabilities in its AI platform, significant additions to the company’s management team, and continued acknowledgement of its leadership through industry awards and analyst recognition. Conversica automates business conversations through virtual assistants powered by artificial intelligence. The company’s flagship AI Sales Assistant engages every lead in a human conversation to qualify more of them for sales, freeing sales reps to spend more time closing business. In the first half of 2017, more Conversica customers than ever employed their AI Sales Assistants to engage and qualify leads and create sales opportunities more quickly, efficiently and cost-effectively. Increased annual recurring revenue by over 50 percent, with sales to new customers and significant expansions in existing accounts. Grew the customer base to over 1,200 companies, adding customers in a variety of industries, such as technology, financial services, education, hospitality and automotive. New customers include Box, New Relic, Microsoft, Northwestern Mutual, Salsa Labs and Avalara.
We also learned of a number of new partnerships, alignments and collaborations … Cloudian, an innovation leader in enterprise object storage systems, has teamed with Skymind Inc., the creator of the Deeplearning4j open-source deep-learning library, to create data management solutions for the hyper-scalable data sets necessary for artificial intelligence (AI) and machine learning (ML) use cases. Under the partnership, the two companies will collaborate on integrated, enterprise-ready AI/ML solutions. Cloudian will provide the limitlessly scalable on-premises storage systems that bring hyperscale technology to the data center, while Skymind’s Deeplearning4j recognizes patterns in massive amounts of data to provide actionable intelligence for companies. Industries benefitting from the Cloudian/Skymind partnership will include health care, fraud detection for financial services, security, robotics and others … oneclick AG has partnered with Fusionex, an IT software group that specializes in analytics and Big Data, to deliver efficiency and cost savings for enterprise systems integrators by imbuing state-of-the-art analytics capabilities to enhance oneclick’s platform. The partnership will see Fusionex’s award winning analytics and Big Data software integrated into oneclick AG’s platform for the automated and secure deployment of digital work spaces … Quantum recently announced its partnership with Veritone, a provider of artificial intelligence insights and cognitive solutions. Bundling Veritone’s technology with Quantum’s StorNext shared-storage will allow users to leverage technologies including optical character recognition, object detection and speech-to-text transcription in on-premise storage. By keeping the AI processing behind the local firewall, Veritone’s platform adds new options for companies concerned about latency, cost or security when it comes to cloud storage … KPMG announced that it has joined the Industrial Affiliates Program with UCLA’s Computer Science Department, becoming one of the biggest professional services firms to join the program. KPMG data scientists will team with some of the world’s leading faculty and students in computer science to engage in significant academic research. KPMG will contribute to the UCLA Computer Science Department by speaking at department research seminars, participating in research reviews, sponsoring knowledge exchanges for faculty and students, and assisting in developing research efforts to explore areas of joint interest, including large-scale machine learning and data and analytics. The firm will also have the opportunity to share its work with the Computer Science Department and interact with student groups and graduate students on a regular basis. In addition, KPMG will be assigned a faculty liaison which will help the firm connect to research at the university.
We learned of some new industry findings from the 2017 Progress Data Connectivity Outlook global survey. In the 4th annual survey based on responses from 1,200 business and IT professionals around the world, the results validate the explosive growth seen in SaaS data sources and the common challenges faced when trying to connect to data in a hybrid environment. Some of the main findings include:
- Big Data adoption increased from 50% to 61%
- SaaS adoption increased from 62% to 79% since last year
- Hadoop Hive is the most popular big data interface and is expected to grow 8% in the next two years
- More than 50% use NoSQL, with MongoDB being the most popular
- The number one integration challenge is an increasing number of data sources
- Almost 100% use data access standards, and adoption is increasin
- OData, the industry standard REST API, is growing in popularity
- 63% use reporting and analytics tools, giving rise to open analytics
- More than 66% must comply with data protection laws
In the new customer wins department, we learned … Open-Xchange, creator of open source messaging and office productivity software for hosting, service provider and telco companies, announced that it has deployed Hazelcast, the leading open source in-memory data grid (IMDG) with hundreds of thousands of installed clusters and over 39 million server starts per month, to implement effective new distributed session storage capabilities for OX customers … Supercomputer leader Cray Inc. (Nasdaq:CRAY) announced it has delivered a Cray® CS™ cluster supercomputer to Embry-Riddle Aeronautical University in Daytona Beach, Florida. The four-cabinet Cray CS400™ system will power collaborative applied research with industry partners at the University’s new research facility – the John Mica Engineering and Aerospace Innovation Complex (“MicaPlex”) at Embry-Riddle Research Park. Embry-Riddle Aeronautical University teaches the science, practice, and business of aviation, aerospace, and engineering. The curriculum at Embry-Riddle covers the operation, engineering, research, manufacturing, marketing, and management of modern aircraft and the systems that support them. The University engages in extensive research in astronautics, space and atmospheric physics, space vehicles, commercial space operations, as well as unmanned and autonomous aerial, land, surface and underwater systems. The University’s new Cray CS system, named “Vega”, which is the fifth brightest star in the sky and the second brightest star in the northern celestial hemisphere, is currently in production and will substantially enhance the University’s position to attract and conduct both applied and theoretical, externally funded research. Vega will play an important role in Embry-Riddle’s efforts to build new collaborations between the University and aerospace companies to develop, refine, and bring new products and technological services to market … Snowflake Computing, the only data warehouse built for the cloud, announced that Runkeeper, a leading mobile fitness app, chose Snowflake to give its business analysts rapid access to data-driven insight to deliver new and engaging features of the Runkeeper app. Using Snowflake, Runkeeper’s analytics performance is now more than 135 times faster than before. Millions of users across the world rely on Runkeeper to track workouts, set goals, and connect with the community to stay motivated. Every time users create events, such as starting a run, sharing with a friend or responding to a push notification, they generate data that helps Runkeeper understand how to improve the customer experience. Prior to going live on Snowflake, Runkeeper’s previous data warehouse presented them with a series of ongoing difficulties related to concurrency and the ability to get information into and out of the platform quickly.
And finally, our friends over at data virtualization (DV) provider Denodo. had some interesting takes on the industry. Synonymous with information agility, data virtualization delivers a simplified, unified, and integrated view of trusted business data in real time or near real time as needed by the consuming applications, processes, analytics, or business users. It integrates data from disparate sources, locations and formats, without replication to create a single “virtual” data layer that delivers unified data services to support multiple applications, users and technologies. The result is faster access to all data, less replication and cost, more agility to change. Denodo executives offered the below trends:
- Capitalizing on In-memory Computing: In-memory computing is now being touted as the antidote for slow disk-access technologies. It is expected to grow from almost $7 billion in 2016 to a whopping $34 billion by 2022 – a CAGR of 30+% according to the market research firm Mordor Intelligence. Many technologies like the database and data virtualization are getting on the bandwagon to cure the slow BI illness. By moving the processing to in-memory, these technologies can process very large volumes of data at a very high velocity. This article will discuss the in-memory technologies, its adoption by technologies like database and data virtualization, and the new use cases and benefits for companies.
- Understanding the Impact (and Benefits) of Edge Computing: Edge computing is the ability to move the processing of data to the edge of the network, near the sources where the data resides. This improves performance because most of the processing is done at the sources and only the results need to be moved to the destination, thus reducing the amount data that needs to be moved through the cloud. Previously, massive amounts of data were moved over the wires, causing bandwidth constraints, to a centralized location like a data warehouse. This approach of pushing the processing to the data sources is a concept that is borrowed from technologies like data virtualization which have been using push down processing to execute the queries in the source and bring back only the results, thus improving performance. This article will discuss edge computing, how data virtualization uses edge computing, and benefits to the business community.
- How Machine Learning Can Drive Integration Automation: Although machine learning presently occupies only a minor role in data integration, it is poised to accelerate in importance given its potential to drive automation within the framework of the modern data integration paradigm. Currently, there are two ways that enterprises are leveraging machine learning in data integration. One approach is embedding machine learning components in integration flows or pipelines to support real-time analytics and decision making. The other approach is leveraging machine learning to minimally automate the integration components.
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