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
Year End Special! In this edition of our popular “Above the Trend Line” column we’ll feature a number of 2019 prediction commentaries received from our friends in the big data ecosystem. Don’t miss these insights by industry luminaries from well known companies.
We’ll start off with some new funding news … Enterprise AI solutions company CrowdANALYTIX announced that it has secured a significant strategic investment from Macnica, a leading global supplier of semiconductors, electronic components, network equipment, and software products in the electronics and IT markets. The investment will enable CrowdANALYTIX to venture into the important Japanese market as well as several new industry sectors, including manufacturing and healthcare, where Macnica has a strong presence. Founded in 1972 in Tokyo, Macnica is a subsidiary of Macnica Fuji Electronics Holdings, Inc. (TYO: 3132). The company has 3000 employees in 22 countries including Japan, China, Asia, North America, South America, and Europe. After seeing CrowdANALYTIX’s unique capabilities as a leading enterprise AI platform and its strong growth trajectory, Macnica decided to make the investment as part of a broader corporate initiative to expand its AI business segment … GeoSpock® – the extreme-scale spatial big data integration company that provides analytics, builds insight, and enables predictions across space and time – announced it has raised £10 million in additional funding, bringing the total raised to date to £19.25 million. Investment was led by existing backers Cambridge Innovation Capital (CIC) jointly with Parkwalk Advisors and Japanese firms Global Brain and 31Ventures. Japanese data tech company KDDI Supership joined as a strategic investor. Investment was also secured from existing investor, Jonathan Milner. The additional funding will support GeoSpock’s rapid international expansion strategy to help develop key client accounts, particularly in the strategic markets of Singapore and Japan. The investment will also allow the spatial big data company to continue to invest in research and development, particularly in the areas of machine learning and data science. GeoSpock is fast establishing itself as the de facto processing engine at the heart of next-generation smart infrastructure – including smart cities and the Internet of Everything (IoE). The company powers future mobility applications, including the management of autonomous vehicle fleets, working with businesses across the automotive, telecoms, mobility, marine, media, and retail sectors.
We also heard of some new partnerships, alignments and collaborations … Skuid, a leading no-code cloud application platform, announced it has joined the MuleSoft Technology Partner Program so enterprises can create even better business applications. With Skuid and MuleSoft, customers can deliver highly usable business applications that unlock customer’s data across the enterprise and enhance user experiences to drive business productivity—all without costly and lengthy development cycles. As enterprise stacks diversify by adding more cloud and on-premise systems, companies need to join their disparate data sources in meaningful ways to create useful applications. Access to the appropriate real-time data can help customers, partners and employees get things done faster and more intelligently, while delightful user experiences make applications more useful and enjoyable for all. The combination of the Skuid and MuleSoft solutions allows organizations to quickly and securely share data, regardless of format or source, and to transform that newly unlocked data into useful and delightful applications. MuleSoft’s Anypoint Platform™ provides APIs and integration capabilities to connect nearly any technology in a standardized way, while the Skuid platform delivers a comprehensive front-end application development system to design, build and deploy rich user experiences … data Artisans is joining forces with Alibaba to build a new initiative around Big Data open source technologies, following a Series B financing round earlier last year. The company is thrilled about this move and the exciting future that lies ahead for their customers, partners and the Apache Flink and broader Big Data open source community. Since data Artisans was founded in 2014, the company has always been believers in the potential of open source technologies for developers and enterprises. That’s why they started Apache Flink as an open source framework for efficient, yet user-friendly data processing at massive scale. Fast forward to January 2019 and Flink is one of the fastest growing communities in the Apache Software Foundation, with hundreds of contributors and astonishing adoption by some of the largest companies in the world from multiple industries and geographies. Especially at times when many open source technologies and companies decide on a less collaborative and more “closed” approach, it is with great pleasure to see Alibaba committed to open source and data Artisan’s mission, eager to take Flink’s technological advancement to the next level. Alibaba, as one of the largest production users and biggest contributors to Apache Flink, in close collaboration with the open source community and data Artisans team, has made numerous contributions to the Flink codebase over the last 2 years … WorkAround, a crowdsourcing platform for refugees and displaced people, partners with BigML, the leading Machine Learning Platform accessible for everyone, to give more economic opportunities to end users. In a world of increasing automation, it is easy to forget the human work that goes into making Machine Learning happen. Quality data is the linchpin to accurate outcomes from Machine Learning algorithms, but finding providers that can deliver clean and accurate data is challenging. However, WorkAround makes this possible while working with skilled refugees and displaced people who are otherwise unable to work due to government restrictions, lack of access to banking, and other barriers. With this partnership, BigML customers will enjoy the benefits of having their data cleaned and tagged without the burden of having to perform these tasks by themselves, thus being able to dedicate more time to other strategic tasks.
In the new customer wins category, we learned … Hush, an online beauty retailer, similar to Ulta or Sephora, has begun using the Alteryx platform to personalize the in-app experience of its customers. With Alteryx, Hush has been able to build predictive models, which has transformed their push notifications with real-time machine learning. The models “learn” how customers feel and behave, what they engage with on the site, etc. so that any push notifications that are sent out, are tailored to that specific customer. Hush has seen a 3x increase in sales from this one use case, and they see potential to bring these models throughout the company … OpenText™ (NASDAQ: OTEX, TSX: OTEX), a global leader in Enterprise Information Management (EIM), announced that leading international law firm Pillsbury Winthrop Shaw Pittman LLP will be the first law firm to deploy OpenText Magellan, OpenText’s AI-enabled analytics platform. Pillsbury will leverage Magellan to deliver expanded automation and artificial intelligence enhancements to the firm’s global legal practice … Snowflake Computing, the data warehouse built for the cloud, announced that Strava, the GPS tracking app and social network for athletes, uses Snowflake to power its business. Switching to Snowflake has significantly reduced the data engineering resources required to manage the company’s data, resulting in more engineers focusing on developing additional services for Strava’s athletes and more focus on building its global community. Since its founding in 2009, 35 million cyclists, runners, hikers and other athletes in 195 countries have joined the community of San Francisco-based Strava (Swedish for “strive”). The company’s free mobile apps and website help members discover and plan workouts, record and share activities, and analyze and compare performance. Strava’s ability to connect athletes around the world makes fitness a more social experience, providing a source of motivation and inspiration even when training alone.
In people movement news we heard … Collibra, a leader in enterprise data governance and catalog software, announced the appointment of Jim Cushman as Chief Product Officer, a new role for the company. An accomplished senior executive with a strong track record of innovation and growth, Cushman will drive the firm’s product portfolio to support customers on their digital transformation journey … Dstillery, a leading applied data science company serving the marketing & advertising industry, has promoted Melinda Han Williams to Chief Data Scientist. At the helm, Williams will continue to lead Dstillery’s world-class Data Science & Analytics team, driving strategic company initiatives, product innovation and bridging the industry’s thought leadership gap around the power of data science, artificial intelligence and machine learning for brand marketers and insights professionals.
2019 Predictions
There will start to be a more standard set of best-in-class tools for the data scientists and miners looking for AI gold,” said Scott Clark, CEO and Co-founder of SigOpt. “In the next year, we’re going to see a lot more companies adopting and seeing impact from AI and machine learning technologies. As a result, an influx of data scientists and experts will need to be trained and hired. To combat the predicted 2,720,000 open data science positions, organizations will need to provide their experts with tools that help improve practitioner productivity so that they’re empowered to achieve their full potential. Not only will adoption of these tools increase, but by year-end there will start to be a more formalized, standard set of best-in-class tools that define whether a company is or is not set up for AI success.”
Not all data is created equal,” said Dr. Werner Hopf, SVP Data and Document Solutions at Serrala. “We will continue to see customers with extremely large databases because of the mindset that all the information gathered could potentially be valuable. To take advantage of big data, companies will need to put a plan in place to control data growth by identifying which information is truly valuable to the company. Much of the older data that companies are holding on to can be archived and eventually purged. By keeping control of big data growth, companies can free up time and funds that can be dedicated to big data projects that will drive the future of the business.”
Investments in business intelligence/data analytics solutions will continue to rise in 2019,” said Ashish Thusoo, co-founder and CEO of data analytics firm Qubole. “With the continued emphasis on data analytics as a differentiator for business, there’s no question that investments in BI will increase next year, as borne out by predictions from IDC and others. The interesting question is where will the focus be. I expect to see an uptick in streaming data analytics, as businesses try to leverage real-time information to make smart decisions in areas like customer support, marketing, fraud detection and upselling customers. There will also be growth in ad hoc analytics, as cloud services mature to allow a wider range of analysts and business decision makers to make use of analytics however they need it. This continues the democratization of data theme that we heard so much about in 2018.”
Artificial intelligence and the internet of things promise limitless connectivity, complete automation and immersion into extended realities,” said Gianfranco Lanci, Lenovo President and COO. “The adoption of these intelligent offerings will continue to scale into different verticals from manufacturing to education, retail and more in 2019. In fact, according to a recent Accenture study, 72 percent of health executives agree that extended reality will be widespread and impact virtually every industry over the next five years. In the healthcare sector for example, IoT and artificially intelligent enhanced applications can solve some of humanity’s greatest challenges. Leveraging these technologies has the potential to unlock a wealth of developments in coming years. Reducing emergency waiting room times, enabling remote health care and monitoring, offering the availability and accessibility of critical hardware, and even freeing up doctors’ time through the use of AI in detecting and diagnosing tumors are all examples. In fact, according to a recent Market Research forecast, the IoT healthcare sector will continue to expand significantly, reaching US$163.24 billion by 2020, a 38 percent compound annual growth rate from 2015. Retail is also going through a transformation, with new ways to identify and engage customers early in the shopping experience, as well as enabling customers the freedom to purchase flexibly, whether via mobile, self-checkout, online or regular checkout. The drive to unified commerce applications in retail is leading a revolution in transactional point-of-sale devices. These devices integrate with point-of-experience interfaces for customer loyalty programs and IoT offerings to enhance retail with new technology in real-time pricing, inventory management and customer analytics. As new advances and applications make their way into various verticals, expect to see accelerated adoption as technology costs come down and organizational and business outcomes improve.”
Open source is playing a critical role in modern IT infrastructure and IT businesses, a fact that’s not going unnoticed by the major cloud vendors,” said Karthik Ramasamy, Founder of Streamlio. “Recent open-source moves by AWS (AWS App Mesh, Amazon Managed Streaming for Kafka), the IBM acquisition of Red Hat and the VMware acquisition of Heptio are the latest data points illustrating that these major vendors are not only looking to more actively play in this space, but potentially looking for ways to co-opt the open source ecosystem. The fear has only grown that big cloud providers will undermine open source communities and vendors by launching their own closed cloud services based on open source without contributing back to those communities. However, there are signs in these recent moves that big vendors are taking a nuanced approach—in some cases working to co-opt open source to the ecosystem’s detriment while in other cases supporting vibrant open source ecosystems. For instance, the recently released Amazon Managed Streaming for Kafka (Amazon MSK) is likely to have negative repercussions for the Apache Kafka ecosystem even as Amazon’s open source Firecracker aims to establish an open source community and ecosystem around it. This trend will accelerate in 2019 and beyond, and the extent to which these companies act as ‘good citizens’ within open source will bear watching.”
Companies serious about machine learning and artificial intelligence (AI), while perhaps in the early stages, have a multi-year approach to data acquisition and strategy in place, focused on compiling data from different sources and silos—often within a Center of Excellence (COE)—that will ultimately drive the AI revolution,” said Langley Eide, Chief Strategy Officer at Alteryx. “At the same time, cloud-forward organizations are looking to offerings from companies like Amazon, Microsoft and others to create intermediate data storage that can support diverse analytic use cases and evolve as strategies progress. To help prepare for the AI-driven future, organizations need to ask questions like: What data is available and is it accessible? What data do I need to acquire externally to drive competitive differentiation? Is my data available in a way that can be readily available for machine learning? And, perhaps most importantly, how that work needs to get done: How do we upskill our line-of-business (LOB), what requires pure data science know-how and what can the IT organization manage? In 2019, organizations need to answer these questions (and fast) before they can realize the true potential of AI.”
We expect that machine learning will reach the tipping point of practical acceptance in 2019,” said John Nash, Chief Marketing and Strategy Officer at RedPoint Global. “Over the past year, there has been a transition from theoretical to practical application around machine learning, driven by the production of tangible results. Analytics that marketers and non-technical staff can manage is here and now – ready for prime time, models for the masses. A shortage of data scientists will remain, which will also help drive “managed AI” as an effective alternative approach.”
Machine Learning will not only be used to build smarter applications, but also to build applications smarter,” said Hans de Visser, VP Outbound Product Management at Mendix. “In 2018 the first AI-assisted programs in the low-code space were launched. Low-code platforms render ideally for AI-assisted development as low-code abstracts from lower level technology using patterns to define the application domain, UI and logic. Since most low-code platforms are cloud based and hold millions of models in their repository, anonymized models are the ultimate source for neural network-based ML to guide developers while they are building application models. 2019 will be a break-through year for AI-assisted low-code development.”
Holistic Analytics: Business sponsored data management driven initiatives will increase as organizations develop greater commitment to the data value chain for analytics use,” said Information Builders COO, Frank Vella. “As analytics environments become more mature, the emphasis on strong data quality, MDM, and other data-related initiatives increase. Organizations will start looking at these initiatives as an integral part of their analytics strategy and not as something external or complementary to BI.”
In 2019 AI will go mainstream, measurably saving lives and extending lifespans because of improved monitoring of patient genetics, habits and medical records,” said Dr. Alex Zhavoronkov, Founder of Insilico Medicine. “Pharmaceutical companies, slow to adopt artificial intelligence so far, will face a tipping point in 2019, partnering with startups or buying AI companies outright to dramatically improve their inefficient drug discovery process. Every year, big pharma companies spend over $172 billion on research and development. Yet, despite that huge investment, 90% of the drugs they discover using traditional techniques fail in human clinical trials. AI will improve the odds of finding new drugs faster and more affordably to treat patients with cancer and other diseases.”
Enterprises unable to leverage their data will face extinction,” said Manish Sood, CEO of Reltio. “It’s that simple. Some estimate that half of S&P 500 companies will be replaced within the next decade. Companies that don’t evolve according to new customer expectations or develop innovative business and revenue models will become a part of these stats. Having a well-thought-out data strategy will be required to survive and thrive in 2019.”
The forecast for 2019 looks very cloudy,” said James Brown, CEO of Smart Communications. “And that’s a good thing. In 2016, IDC reported that 85% of enterprise decision makers felt they had a time-frame of just two years to make significant inroads on their digital transformation before suffering financially and/or falling behind their competitors. We have certainly seen tremendous progress toward that goal, but there is still a way to go before many enterprises, especially those in highly regulated industries, are able to fully deliver on their customers increasingly digital demands. And I believe 2019 is going to be the year in which this adoption explodes.”
As more organizations look to their data for business advantage, we will see further investment in self-service analytics and machine learning capabilities and tools, empowering the business user as data scientist while also overcoming shortages in specialized staff and to address the ever-increasing demand to base decisions upon advanced analytics,” said Rami Chahine – Vice President of Product Management, Datawatch, an Altair company.
AI has transformed industries like manufacturing and agriculture, but that doesn’t mean that the buzz of AI will continue in 2019,” said Darin Archer, CMO at Elastic Path. “The joke going around Silicon Valley is that you’ll now get kicked out of a pitch if you bring up AI because it’s such over used hyperbole. The reality is that much of the hype is unachievable by the vast majority of organizations. There’s a limited talent pool of data scientists and they get scooped up by the tech giants. You also need massive amounts of richly codified training data, which is impossible for most organizations. They can barely connect data about their consumers across channels. Most of the AI buzz from software companies like IBM and Salesforce amounts to no more than the evolution in ‘natural language processing.’ We now excel at text-to-speech and speech-to-text, but what we do with that content once wonderfully transcribed from voice still needs to be developed. I think AI is dead until we refocus on the purpose of the technology, and how it can improve specific functions like customer experience or software. Or at least we’ll stop talking about it with empty statements and start talking about business problems and business outcomes again. I hope.”
Hybrid computing gives the best of both worlds, allows you to run legacy workloads or compliance sensitive workloads in tandem with newer cloud native technologies,” said Marty Puranik – Founder, President and CEO of Atlantic.Net. “Hybrid expedites data transfers because you can attach or move storage directly to it. For public cloud, you will have to upload it which can be very slow and tedious. Advanced security features can be implemented in a hybrid environment because you have total control of the infrastructure, so for example if you want to directly attach security devices you can. With public cloud, the security devices would be limited to what the cloud provider has integrated into the platform. Even then, you don’t know how many things may be in between the devices, whereas with hybrid you can control a physical infrastructure for security sensitive data, and then use public cloud for web-facing workloads.”
The coming twelve months will see a few new trends, including the rise of 5G wireless technologies at a consumer level,” said Infogroup CMO Tony Marlow. “This will drive a spike in the everyday proliferation of connected ‘things’ beyond mobile devices and will also drive an associated spike in the data that this next-gen ‘internet of things’ will generate. This data spike will be vast, and it will feed into the delivery of better products and experiences as well as better communications between brands and people. From a marketer’s perspective, this flood of data will push a realization that having access to lots of data is different from working with high quality data. Even more importantly, we will see the industry appreciate the difference between data quantity and gleaning intelligence from that data, and why it is important to have this intelligence feed into curated, clean and real-time marketing experiences. Basically, we will very likely see marketers move from an interest in big data to an obsession with extracting intelligence. This means that 2019 will be the year of intelligence based marketing and CMOs and CROs everywhere will be looking for partners to help them navigate this terrain.”
Data is currency and successful businesses must structure data and content for modern technologies and platforms, particularly if they want to start applying artificial intelligence to their data,” said Tammy Bilitzky, CIO of DCL.
Forget the AI winter, the AI spring is here,” said Lexalytics’ CEO, Jeff Catlin. “We’ve heard plenty of rumblings about the inevitable AI winter, a time of reduced funding and interested in AI research. But the much-prophesied winter seems to be a long time coming. Instead, we’re seeing significant AI investment and high expectations about the growth that AI will deliver in the coming years. Rather than an AI winter, next year is more likely to bring us an AI spring – which is good news for all of us in the industry.”
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