“Above the Trend Line” – Your Industry Rumor Central for 12/24/2019

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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, 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.

As we prepare for the holidays and a bit of a year-end slow down, we’ll start with some people movement news … MariaDB® Corporation announced Susan Repo as the company’s first Chief Operating Officer. Repo joins after leading an auto fintech startup and spending five years at Tesla, where she steered the company through its hyper-growth global expansion of electric vehicles and sustainable energy products. At MariaDB, Repo will draw on that experience to oversee and accelerate the company’s business operations as it delivers on new product innovations … Yellowbrick Data, the modern data warehouse built for the hybrid cloud, announced the appointment of Jeff Spicer as the company’s Chief Marketing Officer. With more than 20 years of experience in data and analytics technologies, Spicer will focus on accelerating the adoption of the Yellowbrick Data Warehouse and elevating awareness of modern data warehouse solutions … Snow Software, a leader in technology intelligence solutions, announced Paula Darvell has been named Chief Marketing Officer. Darvell will oversee worldwide marketing efforts, reporting into President and CEO Vishal Rao. The announcement follows the appointment of former CMO Sanjay Castelino to Chief Product Officer.

In the new partnerships, collaborations, and alignments we heard … GoodData®, a leader in end-to-end analytics solutions, announced that it is partnering with KMS Technology Solutions (KMS) to expand GoodData’s rapidly growing global footprint and extend its data analytics solution to more parts of the world. The move underscores GoodData’s belief that data analytics should be available to every company, large or small, and that high-end analytics should be a mainstay of data housed in the cloud, on premise or both.

2020 Trends/2019 Year-in-Review

“In 2020 and beyond, companies will begin automating data scientist roles for ML,” commented Steve Phillpott, CIO, Western Digital. “There are simply not enough data scientists in the world to support the growth of ML workloads. Companies are now developing ways to put the power of ML into the hands of software engineers and/or business subject matter experts. New off-the-shelf tools will be able to fulfill the baseline role of the data scientist, and true data scientist roles will shift to higher-level value-add such as fine-tuning ML for specialty use-case work. In 3-5 years, ML automation will become the norm, and companies will have more tools at their disposal to empower data scientist personnel to be more efficient and agile.”

“Massive amounts of data are generated from a diverse set of industry domains, including social networks, e-commerce, transactions, IoT devices and web applications, requiring organizations to react quickly to extract value from that data,” commented Infogix. “Traditional batch processing, where data is sent on a schedule from system to system, will not meet the demands of the changing data landscape. Companies are increasingly turning to event-driven architectures to handle growing volumes of streaming data. They are using distributed streaming platforms like Apache Kafka, ActiveMQ, Apache Pulsar, Amazon Kinesis and many others to provide high-throughput, low latency real-time streaming, flexible data retention, redundancy and scalability. In a world that demands lightning-fast speed-to-insights and real-time access to data, data quality has never been so important. Organizations must enlist vendors who can safeguard data quality to prevent data assets from becoming liabilities and provide validation at a speed and scale to match their data-in-motion.”

“Low code and no code user interfaces will continue to make major inroads among non-developers who are more focused on achieving an end result than they are on how it’s done,” commented Travis Depuy, Product Evangelist at xMatters. “By abstracting the technical layers of a software platform and presenting its features in a more easy-to-use, often drag-and-drop UI, users experience all the benefits more quickly, without having to be steeped in software languages and architectures. This is not to say the seasoned developer will be overlooked. Access to command line interfaces will still be available. In 2020 the majority will choose the low code solution, and this will be true whether on-premises or in the cloud, where abstraction will allow for microservices (containers and orchestration systems) to run across multiple clouds simultaneously.” 

“We are living in a world that is increasingly data-driven, and that data is being generated outside of the four walls of the traditional data center,” commented Alan Conboy, office of the CTO, Scale Computing. “With 2020 approaching, organizations are taking a much deeper look at their organization’s cloud usage. Cloud was originally positioned as the answer to all problems, but now the question is at what cost? More organizations are turning to hybrid cloud and edge computing strategies, turning to solutions that process data at the source of its creation. In 2020, organizations will rely on hybrid environments, with edge computing collecting, processing and reducing vast quantities of data, which is then later uploaded to a centralized data center or the cloud.”

“My prediction here is that as in 2019, when AI was the buzzword, in 2020, NLP will be the buzzword,” commented Pat Calhoun, Espressive CEO. “In 2019 AI meant everything and there really wasn’t a great way to define it. It could be a chatbot, it could be an autonomous car, it could be RPA. There was a lot of confusion around what AI really meant. I predict that next year, NLP will ride that train. NLP is a well-defined term. The definition of NLP is that it makes a chatbot capable of understanding what someone is expressing using natural language to be able to then provide some form of an action or a response. But the biggest challenge with NLP is there are so many different flavors and what we’ve actually seen is that, to make NLP successful, it requires a large amount of data. If you look at this from the consumer world, Alexa is a wonderful example. The reason Alexa has gotten so much better over time is that it has millions of consumers using it on a daily basis. There is a team of people at Amazon that are responsible for ingesting that data and using that data to tune Alexa to make sure that it gets better over time. Now how does one do that for the enterprise? There’s no single enterprise that has enough data to the scale of what Amazon has to really provide high accuracy to help employees with their questions. My belief is that NLP is going to go down the path of AI where there’s a lot of confusion.”

“2020 will be a high water mark in AI acquisitions,” commented Lexalytics CEO Jeff Catlin. “With the stock market at all time highs, large businesses will use pricey shares to purchase technological advantages for the coming decade. Many of these acquisitions will be a clear miss, leading to large write-offs. But a few will completely shift the balance in various industries.”

“Expect to see more major mergers and acquisitions in big data next year, such as HPE’s acquisition of MapR or the Cloudera-Hortonworks merger,” commented Unravel Data CEO Kunal Agarwal. “This activity is great for customers as it gives them more robust platforms and helps avoid vendor lock-in. Enterprises care very little today about which vendor they’re buying from, they just want to make sure the solutions fit their use cases. Personally, I haven’t come across a customer who just uses AWS or just uses Cloudera – they all mix and match. The ongoing rollup of these companies is a natural result of this trend.”

“With a lot of tools and services from Azure, GCP and AWS, many industries will start implementing or at least experimenting with some level of AI implementations for their business use cases,” commented Sanjay Jupudi, President Of Qentelli. “2020 will see more focus on explainable AI, to reduce any bias in the predictions. Data scientists will become an integral part of the product teams and work closely with them to create a data first approach to app development, instead of focussing on making sense of data generated by apps.”

“In order to realize all the benefits of data, organizations must not only collect external and internal data, but also make it accessible and usable in real-time to all employees that handle it — engineers, data scientists, analysts and business users with reliability and extensibility,” commented Girish Pancha, co-founder & CEO, StreamSets. “Next year, we predict it will become especially important in data-driven and self-service organizations like Uber, where intelligence from data is actually changing the status quo for the offerings in their industry.”

“We will see non-relational databases really take off within enterprises in 2020 as developers reject the one-size-fits-all approach of SQL and incorporate more purpose-built databases to handle specific needs and use cases,” commented Paul Dix, CTO and Co-founder of InfluxData. “The fastest user growth is all occurring among non-relational databases and there are now database options that clearly do best with certain categories of data such as object storage, key-value, document graph, and time series data.”

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