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“Above the Trend Line” – Your Industry Rumor Central for 1/27/2020

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 M&A activity, people movements, funding news, industry partnerships, customer wins, 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@insidebigdata.com. Be sure to Tweet Above the Trend Line articles using the hashtag: #abovethetrendline.

I’m invigorated to see another fascinating year of data science ahead in 2020, with so much to look forward to in what I believe is the world’s most rewarding profession! Let’s start off with some new M&A news … Hitachi Vantara, a wholly owned subsidiary of Hitachi, Ltd. (TSE: 6501), announced its intent to acquire the business of privately held Waterline Data, Inc. Headquartered in Mountain View, Calif., Waterline Data provides intelligent data cataloging solutions for DataOps that help customers more easily gain actionable insights from large data sets and comply with data regulations such as GDPR. Waterline Data delivers catalog technology enabled by machine learning (ML) that automates metadata discovery to solve modern data challenges for analytics and governance across edge-to-core-to-cloud environments. Waterline Data’s technology has been adopted by customers in the financial services, healthcare and pharmaceuticals industries to support analytics and data science projects, pinpoint compliance-sensitive data and improve data governance. It can be applied on-premises or in the cloud to large volumes of data in Hadoop, SQL, Amazon Web Services (AWS), Microsoft Azure and Google Cloud environments. Waterline Data’s patented “fingerprinting” technology is the cornerstone of its solutions, removing one of the biggest obstacles to data lake success. Fingerprinting uses AI- and rule-based systems to automate the discovery, classification and analysis of distributed and diverse data assets to accurately and efficiently tag large volumes of data based on common characteristics … Qlik announced the acquisition of RoxAI and its Ping intelligent alerting software to deliver actionable, self-service alerting and workflow automation capabilities that enhance analytics users’ and systems’ ability to proactively monitor and manage their business data in real-time to make faster, insight-driven decisions. Organizations are looking to accelerate business value through data. However, data is always changing. Ping’s self-service intelligent alerts, integrated with Qlik’s leading analytics platform, can immediately notify users through mobile, email and social channels of material changes in their data and the context, triggering decisions and actions immediately. And with Ping, any user can design and create their own advanced alerts around their own use cases – based on their existing dashboards and data – without needing a developer or administrator.

We learned of a number of new funding reports starting with … Augmented data management provider Promethium announced it has raised $6M in funding. The round was led by .406 Ventures with participation from existing investor Zetta Venture Partners. In conjunction with the funding, Graham Brooks, Partner at .406 Ventures, has joined Promethium’s Board of Directors. Promethium will leverage the funding to accelerate its go-to-market strategies and continued innovation of its Data Navigation System™ (DNS), which the company officially announced last October … The adoption of AI-based and augmented analysis tools is on every business priority list in 2020. To maximize on the market opportunity, Outlier announced the close of its $22.1M Series B round of funding led by Emergence, with participation from existing investors Ridge Ventures, Capital One Growth Ventures, 11.2 Capital, First Round Capital, Homebrew, Susa Ventures and SV Angel. Over the last 12 months, Outlier, who uses automated business analysis to help businesses uncover insights in unexpected data behavior, has grown more than 400%. With rising customer demand and increasing market opportunities, the company plans to use the funding to accelerate growth and make strategic hires across its Oakland, CA headquarters and Virginia Beach, VA, and European offices … Epsagon, a microservices application monitoring company, announced a $16 million Series A funding round, bringing the company’s total amount raised to $20M. New investor U.S. Venture Partners (USVP) led the round with participation from previous investors Lightspeed Venture Partners and StageOne Ventures. The new financing will fuel the next phase in Epsagon’s growth, including accelerating product innovation for the company’s automated, distributed tracing technology, and investing in sales and marketing to meet global demand from new and existing customers. Epsagon provides a complete, end-to-end monitoring solution that enables DevOps and engineering teams to monitor, visualize, troubleshoot and quickly fix their cloud applications across any type of microservice — containers, Kubernetes, or serverless workloads. Epsagon’s technology is fully automated for modern environments where the host may not be accessible, which makes traditional monitoring agents obsolete. Epsagon is an AWS Advanced Technology Partner with DevOps, Data and Analytics, and Retail Competencies and can integrate with any cloud provider — AWS, Google and Azure clouds — or Kubernetes clusters in less than five minutes … Placer.ai, a leader in location analytics and foot traffic data, announced the close of a $12M Series A funding round. The round was led by JBV Capital with participation from Aleph, Reciprocal Ventures, OCA Ventures, existing investors and a group of new strategic investors. The funding will be used to help grow Placer.ai’s US operation and expand the company’s R&D efforts to drive new product features and capabilities. Placer.ai’s SaaS platform is the first to provide real-time access to location analytics and foot traffic data. The solution empowers professionals to improve decision making, reduce risk and identify opportunities with accurate, reliable location data … Iguazio, the data science platform for real time machine learning applications, announced that it has raised $24M of funding. The round was led by INCapital Ventures, with participation from existing and new investors, including Samsung SDS, Kensington Capital Partners, Plaza Ventures and Silverton Capital Ventures. The funds will be used by Iguazio to accelerate its growth and expand the reach of its data science platform to new global markets. Cyral, the cloud service for enabling security policies at the data layer, announced the close of an $11 million Series A funding round led by Redpoint Ventures with participation from A.Capital, Costanoa VC, Firebolt, SV Angel and Trifecta Capital. The financing follows a previously undisclosed angel investment round of $4.1 million bringing the total investment raised to date to $15.1 million.

In the new partnerships, alignments and collaborations department we learned … AI-powered visual inspections pioneer Neurala announced a collaboration with drone service provider AviSight to identify defects in critical infrastructure. AviSight’s Live Look Fault Vision™ inspection solution will be integrated with Neurala’s software to flag potential issues in infrastructure such as oil and gas pipelines, wind turbines and cell and electrical towers. By partnering with AviSight, Neurala is able to provide end-to-end service to inspection customers who require a complete solution for drone-based inspections of critical infrastructure, including Beyond Visual Line of Sight (BVLOS) operations … Insilico Medicine is pleased to announce that it has entered into a research collaboration with Pfizer Inc. (NYSE: PFE) to utilize Insilico’s machine learning technology and proprietary Pandomics Discovery Platform with the aim of identifying real-world evidence for potential therapeutic targets implicated in a variety of diseases.

In the new customer wins category, we heard … Anexinet Corporation, a leading provider of digital business solutions, announced that eMoney Advisor (eMoney) has selected Anexinet to expand its production environment across an HPE Synergy platform. This new platform provided eMoney with a network infrastructure aligned with a hybrid IT architecture, along with a long view, future-proof technology roadmap. For more information, please see the full case studyAlation Inc., the data catalog company, announced that DraftKings selected the Alation Data Catalog to help leverage data more effectively to serve users across its sports betting and daily fantasy sports products. With Alation, DraftKings’ data analysts and business users have a centralized, single source of reference for efficient data discovery, effective collaboration, and expanded knowledge-sharing, resulting in better products and superior customer experiences … Iguazio, the data science platform for real time machine learning applications, today announced that Payoneer, the digital payment platform empowering businesses around the world to grow globally, has selected Iguazio’s platform to provide its 4 million customers with a safer payment experience. By deploying Iguazio, Payoneer moved from a reactive fraud detection method to proactive prevention with real-time machine learning and predictive analytics … WekaIO (Weka), an innovation leader in high-performance, scalable file storage for data-intensive applications, announced that Genomics England (GEL) has selected the Weka File System (WekaFS™) to accelerate genomics research for the 5 Million Genomes Project. Genomics England chose WekaFS to meet the predicted capacity scaling that will be required over the coming five years while delivering the highest performance to its DNA pipeline … TigerGraph, the scalable graph database for the enterprise, announced that Ippen Digital, a digital content specialist, has chosen TigerGraph to improve its content recommendation processes to enhance customer engagement and drive digital revenues. Ippen Digital GmbH & Co. KG is a specialist in digital content that develops content strategies and advises companies in handling content on all digital platforms. Ippen Digital is part of Ippen Verlagsgruppe, one of the largest news media groups in Germany with 25 newspapers and more than 60 websites and weeklies … Looker, a leading data platform company, announced that NewWave Telecom and Technologies, Inc., a full-service information technology (IT), business services and data management company, has facilitated the integration of Looker and Snowflake within Microsoft Azure for Government. This powerful data stack for the federal government will transform healthcare for approximately 25 percent of Americans on Medicare and Medicaid by providing transparency into the analytics for identifying treatment baselines. This will ultimately incentivize doctors to meet and exceed these standards.

In people movement news we have … GRAX, a leading data value platform, announced that Morten Bagai has joined the team as the company’s first Chief Technology Officer. In this role, Morten will drive GRAX’s technology vision and execution, guiding the team to build an industry-leading platform for deriving strategic value from data. He will be based in Los Angeles and will report to CEO Joe Gaska. Morten joins GRAX from Salesforce.com, where he served as the Chief Technology Officer of the Salesforce Platform. In this role, Morten helped lead the technology vision for the Salesforce platform and worked with global strategic customers to drive adoption of Salesforce’s application development tools. Prior to that, Morten was the Chief Technology Officer of Heroku, a pioneering platform-as-a-service that runs mission-critical applications for hundreds of Fortune 500 enterprises and startup companies worldwide.

We also received a short commentary on Intel’s Q4 2019 earning report from industry analyst Patrick Moorhead:

“Intel had a great Q4 in spite of increased competition and supply challenges. The ‘data centric’ businesses carried the day with each business driving double digit growth, except for FPGAs. Even PCs were up, which was a big surprise for me. The biggest things Intel needs to do to keep this going is to get out its next generation 10nm designs out and in-market.”

And finally, we heard from Phil Tee, Founder and CEO of Moogsoft, who has published multiple peer-reviewed journals and filed for more than 50 patents in the field of AI, and how he believes only AI is capable of policing AI:

“One of the great challenges for legislatures in the post-industrial age is to stay at pace with technological innovation. In the last few decades, we have been living through this Moore’s law-paced innovation acceleration, and we now find ourselves in a world where the next wave of automation will be conducted by artificial intelligence algorithms which are beyond the comprehension of not just legislators, but actually of most technology specialists. This leads to the more frightening predictions of doom and gloom that you hear. AI regulation needs to be built in a meta way so that AI can be part of its own self-policing, and we need to look to AI innovation to find ways to control and constrain the downside of itself.”

2020 Trends/2019 Year-in-Review

“Now that the retail and travel industries have recognized the usefulness of web data to provide a competitive edge within their sectors, we can expect real estate companies of varying sizes to begin to capitalize on the widely available public data that is available on the world wide web,” commented Gary Read, CEO of Import.io. “Due to the similarities between the real estate, travel and retail industries, there are quite a few ways that real estate businesses can initially take advantage of web data in 2020 – revenue optimization, consumer sentiment, competitor pricing, and more – with additional opportunities yet to be explored.” 

“Industry analyst firm Gartner predicts that 40% of data science tasks will be fully automated by 2020,” commented Dr. Yu Xu, CEO and founder at TigerGraph. “This automation will help business leaders to efficiently plan ahead and use the appropriate analytics to make favorable business decisions. This will be good news for data scientists and analysts who will be freed up from mundane tasks and more able to focus on higher-value activities.” 

“In 2020, we’ll see deepfake technologies migrate from proof of concept and occasional attack tool to a more common tactic,” commented Peter Goldstein, CTO and Co-founder Valimail. “Deepfake audio and video can make cyberattacks against individuals and organizations far more sophisticated and convincing, and therefore, more effective. In 2019, a fraudster used AI voice technology to impersonate the CEO of a German company, convincing an employee to transfer more than $200,000 to the bank of a Hungarian supplier – which was then immediately transferred to another bank in Mexico. It would be foolish to think cyber criminals all over the world didn’t take notice of this incident, and start exploring how they too could leverage this type of technology to reap similar payouts (i.e. delivering messages via Google Voice). Scammers will add deepfakes to their toolkits, combining them with already proven successful techniques, such as phone number spoofing and email impersonation, to advance phishing and BEC techniques and propel increasingly targeted attacks. We predict losses from impersonation-based attacks could be in the billions of dollars in 2020, spurred by an increase in the use of deepfake tech.”

74% of organizations say that conversational assistants are a key enabler of the company’s business and customer engagement strategy,” commented CEO of Voximplant, Alexey Aylarov. “Enterprises are deploying increasingly human-like machine learning and AI-powered chatbots for their customer support strategies. Solutions like Google Contact Center AI, Google Dialogflow and Google Duplex have already displayed the exciting potential of AI that understands intent and interacts in convincingly human ways, which is just the beginning. At the same time, consumers are getting acclimated to the interactive, human-like AIs using natural language, thanks to the increasing prevalence of these interfaces in customer support interactions, home speaker devices, etc. We can expect to see this type of technology evolve even further as enterprises pursue more real-time communications with customers in 2020.”

“There is a skill shortage in the area of database implementation, particularly around the cloud,” commented Matt Yonkovit, Chief Experience Officer, Percona. “More companies want to take advantage of their data, but they are finding it difficult to run operations successfully at the speed that they want to achieve. Developers picking databases to run with their applications just want them to work, without the administrative duties and having to become DBAs to make this happen. Next year, more autonomous database services will become available to meet the need for speed. However, the important thing to be aware of here is how this autonomous service is designed and delivered. What is great for the majority may not be suitable for everyone.”

“To be useful, data needs to be refined,” commented Zira CEO, Elhay Farkash. “Data today if extraordinarily inexpensive and very easy to get. A problem most have never experienced with oil, organizations today are drowning in too much data. A key imperative for 2020 is to focus on acquiring and connecting the right data needed for very specific digital transformation initiatives. It’s about quality over quantity.”

“Amazon has been working hard to deliver SageMaker, a 0 infrastructure development environment for ML models on data stored in Amazon’s Simple Storage Service (S3),” commented Omar Abdala, Chief Data Scientist at Lotame. “With most organizations’ data fully stored in S3 and the new capacity for evaluating models on large datasets using Athena (again with 0 infrastructure), many more companies, even those without extensive Big Data/Data Science teams will be able to dip their toes into predictive modeling. Whereas in the past, there were limitations to the enterprises that could effectively utilize their own data, since it required a large organizational investment, the bar has been lowered to simply hiring a few Data Scientists.”

“Within 5 years we’ll see a significant increase in the % of customers/citizens who will be frustrated when they’re not able to solve an issue either on their own via public knowledge, an automated self-service function, and/or interacting with a chatbot/voicebot,” commented Jonathan Alcabes, Managing Director, Lead – AI Enhanced Interactions, Accenture Federal Services. “This would represent a paradigm shift – today, many look to bypass or get through an automated IVR or chatbot/voicebot to get to a human whereas in the future getting to a human will represent a poor service experience.  Humans will mean something went wrong and will represent inefficiency for the customer/citizen. I also believe we’ll begin to see more examples of true AI, machine learning chatbots vs. Boolean business-rule driven bots which are far more limited and not self-improving.  I believe that in both commercial and eventually public sector contexts, the organizations that are most successful in these efforts will be those that target relatively narrow, fairly repeatable use cases that they eventually scale out vs. general applications where a chatbot would handle most or all of potential customer questions.”

“In 2020, the adoption of in-memory technologies will continue to soar as digital transformation drives companies toward real-time data analysis and decision-making at massive scale,” commented Abe Kleinfeld, CEO, GridGain. “For example, many companies move older data in their operational database to a data lake. There, data scientists can analyze the data on this separate analytics infrastructure. However, this architecture doesn’t work for use cases that require real-time analytics across a subset of operational and historical data. Let’s say you’re collecting real-time data from sensors on a fleet of airplanes to monitor performance and you want to develop a predictive maintenance capability for individual engines. Now you must compare anomalous readings in the real-time data stream with the historical data for a particular engine stored in the data lake.  Currently, the only cost-effective way to do this is with an in-memory “data integration hub,” based on an in-memory computing platform like Apache Ignite that integrates Apache Spark, Apache Kafka and data lake stores like Hadoop. This combination of solutions streams the live data into a transactional database and in-memory computing platform, ingests the relevant subset of historical data from the data lake, and maintains the combined data in memory, where the analytics solution can perform federated, real-time queries across the merged dataset. In addition to predictive maintenance, this platform enables a variety of automated business decision making that instantly reacts to real-time changes in the environment, whether in financial services, healthcare, supply chain and more. 2020 promises to be a pivotal year in the adoption of in-memory computing as data integration hubs continue to expand in enterprises.” 

“Depository banks will accelerate their investments in fintechs,” commented CEO of fintech automation platform, Ocrolus – Sam Bobley. “In 2019 we’ve seen over two dozen major US banks invest in fintechs, almost double from 2018.  As interest rates remain near historic lows and profit margins are squeezed, Banks are looking for growth sectors. Fintechs are well ahead of banks in the areas of data analytics and process automation. While many banks have produced in-house initiatives to build competing services, most will look to invest or acquire fintechs that have developed AI and machine learning-powered processes. In effect, banks are buying into process automation as a strategic investment.”

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