“Above the Trend Line” – Your Industry Rumor Central for 12/11/2018

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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, financial results, industry alignments, 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.

Year End Special! The next several “Above the Trend Line” columns will include a number of 2019 prediction commentaries from our friends in the big data ecosystem. Don’t miss these insights by industry luminaries from well known companies.

Let’s get the ball rolling with some new funding news … Kogniz announced a $4M seed financing round led by The Entrepreneurs’ Fund, Tom Chavez (Krux acquired by Salesforce.com), Auren Hoffman (Liveramp acquired by Acxiom), and other industry investors who are uniquely focused on machine learning and artificial intelligence. After 24 months of development, the Kogniz team has launched its first suite of products that use computer vision and AI to enhance security, safety and efficiency in any physical environment. Kogniz cameras are available today and are live in twenty implementations across the United States. The funding will be used to expand the company’s engineering and data science team, and to grow product distribution … Looker announced it has closed a Series E financing round of $103 million led by Premji Invest, with new investment from Cross Creek Advisors and participation from Looker’s current investors. Looker has raised a total of $280.5 million since 2013. Looker provides the new Platform for Data — streamlining the data supply chain to put real, actionable information into the hands of all employees, when they need it. Looker consolidates fragmented data tools, from data preparation to visualization and cataloging to governance, into a single unified platform that accelerates time-to-insight. Utilizing a simple SaaS approach that leverages fast cloud databases, Looker allows any organization to extract value from their data at web scale. Looker delivers powerful applications through its platform, including Business Intelligence, business-specific solutions such as Digital Marketing Analytics and Web Event Analytics, and a flexible, embedded analytics framework, Powered by Looker. Additionally, Looker empowers a global ecosystem of partners and developers to easily build third-party applications on its platform … FortressIQ, creator of a cognitive automation platform that powers and accelerates digital transformation through imitation learning, announced it has raised $12 million in Series A financing from Lightspeed Venture Partners. This new capital extends $4 million in seed funding from Boldstart Ventures, Comcast Ventures and Eniac Ventures, bringing the total funds raised to date to $16 million. Founded in 2017, FortressIQ pioneered a fundamentally new way for Global 2000 companies to achieve their transformation goals. Recognizing that the largest obstacle to digital transformation is the lack of detailed information on current state of operations, FortressIQ spent 18 months working with corporate transformation teams building AI to solve their most pressing need. This powerful platform addresses Drucker’s age-old maxim that “If you can’t measure it, you can’t improve it,” by delivering the quantified workforce and providing the data today’s enterprise needs to optimize their transformation initiatives … Fivetran, the company that is redefining data pipelines, announced that it has raised $15 million in Series A funding to centralize data for every business as companies execute the move to the cloud. The round was led by Matrix Partners, with general partner Ilya Sukhar joining the company’s board of directors. Primarily revenue-funded since identifying strong product/market fit, Fivetran closed its first venture round after experiencing a 3x increase in revenue and 2x increase in customers over the last 12 months. Current customers include Square, WeWork, Classpass, Vice Media, Lime Scooters, Automattic, Lightspeed, and Kiva … Genomics plc, the data science company specializing in the use of human genetic information to improve drug development, announced that it has successfully completed a second close of its Series B financing round. The second close, which was oversubscribed, raised an additional £8 million, bringing the total raised in the round to £33 million. Both Foresite Capital and F-Prime Capital are large US healthcare investment companies and join previous investors comprising Vertex Pharmaceuticals Incorporated, IP Group, Woodford Investment Management, Invesco Perpetual, Oxford Sciences Innovation, Lansdowne Partners, and Tanarra.

In the new customer wins department we heard … Siemens AG has awarded Accenture (NYSE: ACN) a five-year technology and services contract to run and maintain several of its digital managed services for data analytics and business intelligence. The new project, part of a firm-wide digital and IT transformation effort at Siemens, represents a significant expansion of the ongoing collaboration between the two companies. Siemens is accelerating its digital transformation with help from Accenture’s support for data analytics and business intelligence services … MapR® Technologies, Inc., provider of the industry’s next generation data platform for AI and Analytics, announced that KODAKOne, the blockchain-based image rights management platform, will utilize the MapR Data Platform for a range of data services and digital asset storage. A beta version of the KODAKOne product is due to launch in late 2018. The KODAKOne Platform is an image protection, monetization and distribution platform secured in blockchain. It will provide an image marketplace where users can buy, sell and trade photos based on licensing terms and conditions – serving as a one-stop shop for photographers’ management, protection and distribution needs. The platform will create an encrypted ledger of rights ownership for photographers to protect, manage and monetize their new and archived works – making it significantly cheaper and faster to register, move and sell their digital images. MapR will provide all data services for the KODAKOne Platform, offering enterprise-ready software which can scale as required. The ability of the MapR solution to integrate easily with micro-service based architectures will allow KODAKOne to develop and upgrade the platform with new applications when needed. The MapR platform will help to support overall compliance for KODAKOne internal processing and data access, as well as providing the requisite security features it needs to be fully protected … Collibra – a leader in enterprise data governance and catalog software – announced its partnership with Proximus Group, the largest telecommunications company in Belgium, enabling Proximus to generate strategic value from its data while addressing key regulation and data protection legislations across Europe. Proximus Group provides an array of telecommunication and digital services such as telephony, internet, television and network-based services to residential, enterprise and public customers in Belgium and overseas, through a reliable infrastructure of fixed and mobile networks. Faced with strict compliance requirements set by the GDPR, the Group identified the need to invest in a data governance solution enabling it to find, understand and trust any data asset throughout the organization, for better efficiency and decision making … Western Digital Corp (NASDAQ: WDC) selected Oracle Cloud to help modernize its business processes as part of its digital transformation journey. The company chose Oracle Enterprise Resource Planning (ERP) Cloud in May, 2016 to bring together the core business systems of three multi-billion dollar companies – Western Digital, SanDisk and HGST – all with growth in mind. As a result, Western Digital has been able to combine numerous applications, reduce approval times by 70 percent, rationalize suppliers by 50 percent and improve acquisition agility on a global scale … Anodot, the autonomous analytics company, and professional services firm, Deloitte Australia, announced a strategic alliance to help companies supercharge their real-time analytics capabilities. Deloitte will use Anodot’s AI/ML solution to expand its Consulting Analytics & Cognitive practice’s portfolio of AI-powered service offerings. Bringing together Anodot’s anomaly detection capability with Deloitte’s business advisory, data and analytics capability creates a unique value proposition to help businesses proactively identify and fix anomalous business and technical incidents that would otherwise lead to millions of dollars lost in sales, production or fraud. With vast amounts of data collected across business and IT metrics, it becomes increasingly difficult to track, analyse and derive valuable business insights, especially with traditional Business Intelligence (BI) and do-it-yourself approaches. With Anodot’s autonomous analytics, data is rapidly analysed across all data sources in real-time. Its predictive capabilities detect risks before they reach customers, allowing users to make the right decisions and prevent major crises … Snowflake Computing, the data warehouse built for the cloud, announced that VICE Media, the digital media and broadcasting company specializing in edge content, uses Snowflake to power its business in a multitude of ways. The results of switching to Snowflake include a first-year savings of more than $500,000, re-focusing crucial IT staff from maintenance-only endeavors to strategic technology projects. VICE was launched in 1994 as a “punk zine”​ and has since expanded into a leading global youth media company with more than 3,000 employees and bureaus in over 30 countries. VICE operates the world’s premier original online video destination, VICE.COM, an international network of digital channels, a television production studio, a magazine, a record label, an in-house creative services agency, and a book publishing division.

In the new partnerships, alignments and collaborations we learned … Etlworks, a SaaS start-up helping businesses connect various systems and APIs through the common gateway, has announced its official partnership with online data warehouse, Snowflake. Etlworks data integration solution (connector) is certified by Snowflake and is listed on their website. Etlworks connector is the fastest and easiest way to implement complicated data integration workflows optimized for Snowflake. The flows which use Snowflake connector are highly customizable and can include multiple transformations with all sorts of standard and exotic options: from per-field mapping to denormalization and pivoting … ParallelM, a leader in MLOps, announced a partnership with Cloudera to add options for bringing machine learning (ML) models from Cloudera ML development environments, including Cloudera Data Science Workbench (CDSW) and the upcoming cloud-native Cloudera Machine Learning platform, into production using ParallelM’s MCenter. MCenter allows for centralized management of ML models taking full advantage of existing infrastructure investments so Cloudera customers can start deploying AI applications at scale.

2019 Predictions

While B2B providers have been slow to adapt to the high standard of personalized digital experiences set by Amazon and Google, the industry has at least acknowledged the value of personalized home and landing pages,” said Gal Oron, CEO of Zoomin. “As customer expectations increase, enterprises will need to keep pace by using machine learning and AI to offer a personalized experience beyond the first impression, which extends to other assets such as technical documentation, community portals, and chatbots.”

Data Science claims its place as Strategic Data Command,” said James Markarian, CTO, SnapLogic. “Traditional intelligence tools and platforms do a good job of providing operational insight and reporting. Data science has an opportunity to help with weak signal processing — information that comes from the market, from field personnel and from customer support, and which can guide company strategy towards new opportunities or avoid potential disasters.”

Companies know they must adapt to change in order to grow and stay relevant, but they aren’t relying on enough data to inform change,” said Tom Goodmanson, CEO, Calabrio. “In 2018, we discovered a discrepancy between the value executives place on analytics and the extent to which data is actually analyzed. We surveyed 1,000 executives and found that while nearly all agree that data and analytics are integral to informing sales and marketing changes, more than half of them currently rely on only one data point—such as revenue figures or social media interactions—to inform decisions. They aren’t getting to voice-of-the-customer data to understand what their customers want. In 2019 this will change. ICD estimates enterprises will spend in excess of $2 trillion in 2019 on digital transformations. Companies who lead successful change initiatives will do so by implementing omnichannel analytics from the contact center to get to the root of what customers want. Improvement of data integration and reporting across the business will give the C-suite easier access to data and the knowledge needed to fully optimize customer experiences.”

Auto Labeling – For supervised learning, large sets of human annotated data is needed to train a deep learning model that performs a particular task,” said Atif Kureishy, Teradata‘s Vice President Global Emerging Practices. “A fundamental challenge that the Enterprise faces today in their AI journey is the creation of customized high-quality human annotated data. This process is slow, repetitive, may involve subject matter experts, and at times need to be redone. For enterprises, this is a significant upfront investment with a big risk and big costs. In 2019, we will see a trend towards AI powered tools that assist humans in the creation of high-quality annotated data through auto-labeling techniques. AI involvement at early stages of the journey will reduce cost, risk and help create efficiency: these will play a big role in fueling AI adoption at enterprises.”

The demand for the data scientist will take a sharp turn,” said Kevin Smith, Vice President of Product Marketing at GoodData. “The data scientist, once the sexiest job of the 21st century, will become very different from what we know today. As analytics are pushed to the end user, self-service becomes routine, and data prep tools become more powerful, the data scientist will transform into more of a consultant than a data sourcing and preparation expert. They will be charged with helping the business make sense of data, understanding how to interpret results, and what courses of action might be warranted. It’s a higher value role for the data scientist and ultimately, a better use of their skills.”

Organizations that don’t have good data harvesting are doomed to fail: Research shows that data scientists and analysts spend 80% of their time preparing data for use and only 20% of their time actually analyzing it for business value,” said Adam Famularo, CEO of erwin. “With automated data harvesting and ingesting data from ALL enterprise sources (not just those that are convenient to access) data moving through the pipeline won’t be the highest quality and the “freshest” it can be. The result: faulty intelligence driving potentially disastrous decisions for the business.”

In 2019 Artificial Intelligence (AI) and Machine Learning (ML) will nearly reach its full potential by connecting and processing data faster over a global distribution of edge computing platforms,” said Alan Conboy, Office of the CTO, Scale Computing. “AI and ML insights have always been available, but possibly leveraged a bit slower than needed over cloud platforms or traditional data centers. Now we can move the compute and storage capabilities closer to where data is retrieved and processed, enabling companies, organizations and government agencies to make wiser and faster decisions. We’re already seeing this in the way airlines build and service airplanes, government defense agencies respond to hackers and how personal assistants make recommendations for future online purchases. This year, thanks to AI and ML, someone will finally know if that special someone really wants a fruitcake or power washer.”

2019 seems as if it will be the year of analytics, machine learning and AI,” said Stephen Gailey, solutions architect, Exabeam. “These tools are already available, though their take up has often been delayed by a failure to match these new capabilities with appropriate new workflows and SOC practices. Next year should see some of the pretenders – those claiming to use these techniques but actually using last generation’s correlation and alert techniques in disguise – fall away, allowing the real innovators in this field to begin to dominate. This is likely to lead to some acquisitions, as the large incumbents, who have struggled to develop this technology, seek to buy it instead. 2019 is the year to invest in machine learning security start-ups demonstrating real capabilities.”

Some existing applications that we may see more than others in 2019 will be chatbots and increasingly autonomous vehicles,” said Scott Parker, Director of Product Marketing, Sinequa. “The improvement in chatbot AI capabilities, will create an opportunity for innovative customer service groups to step up in 2019 over competitors. 2019 will also be a big year for autonomous driving initiatives to leverage empirical data with continuously improving algorithms and hardware processing power.”

As AI and ML become mainstream, a new breed of security data scientists will emerge in 2019: AI and ML techniques are data dependent,” said Setu Kulkarni, Vice President of Corporate Strategy, WhiteHat Security. “Preparing, processing, and interpreting data require data scientists to be polymath. They need to know computer science, data science, and above all, need to have domain expertise to be able to tell bad data from good data and bad results from good results. What we have already begun seeing is the need for security experts who understand data science and computer science to be able to first make sense of the security data available to us today. Once this data is prepared, processed and interpreted, it can then be used by AI and ML techniques to automate security in real time.”

In software development, the big story in 2019 will be machine learning and AI,” said Bob Davis, CMO, Plutora. “In the coming year, the quality of software will be as much about what machine learning and AI can accomplish as anything else. In the past, delivery processes have been designed to be lean and reduce or eliminate waste but to me, that’s an outdated, glass-half-empty way of viewing the process. This year, if we want to fully leverage these two technologies, we need to understand that the opposite of waste is value and take the glass-half-full view that becoming more efficient means increasing value, rather than reducing waste. Once that viewpoint becomes ingrained in our M.O., we’ll be able to set our sights on getting better through continuous improvement, being quicker to react and anticipating customer’s needs. As we further integrate and take advantage of machine learning and AI, however, we’ll realize that improving value requires predictive analytics. Predictive analytics allow simulations of the delivery pipeline based on parameters and options available so you don’t have to thrash the organization to find the path to improvement. You’ll be able to improve virtually, learn lessons through simulations and, when ready, implement new releases that you can be convinced will work. Progressive organizations, in 2019, will be proactive through simulation. If they can simulate improvements to the pipeline, the will continuously improve faster.”

As big data continues to proliferate, there will be an increasing need in 2019 for technology that enables personal and contextual access,” said Scott Parker, Director of Product Marketing, Sinequa. “While technology continues to drive the creation of big data next year and beyond, new innovations will increasingly help people and organizations leverage big data to enable users to make better informed decisions. An area to keep an eye on next year is also the increasing focus on privacy around big data. GDPR and the California Consumer Privacy Act were just the beginning, and I expect to see more privacy regulation discussions next year.”


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