An unfortunate side effect of being an industry analyst is that it is easy to become jaded. There is a tendency to fall back into stereotypes about technology and companies. Add to this nearly 35 years in computer technology and it would surprise no one to hear an analyst say, “Been there, done that, got…
On a monthly basis, I will be rounding up key news associated with the Data Science Platforms space for Amalgam Insights. Companies covered will include: Alteryx, Anaconda, Cloudera, Databricks, Dataiku, DataRobot, Datawatch, Domino, H2O.ai, IBM, Immuta, Informatica, KNIME, MathWorks, Microsoft, Oracle, Paxata, RapidMiner, SAP, SAS, Tableau, Talend, Teradata, TIBCO, Trifacta.
On August 15, 2018, Oracle announced the availability of GraphPipe, a network protocol designed to transmit machine learning data between remote processes in a standardized manner, with the goal of simplifying the machine learning model deployment process. The spec is now available on Oracle’s GitHub, along with clients and servers that have implemented the spec for Python and Go (with a Java client soon to come); and a TensorFlow plugin that allows remote models to be included inside TensorFlow graphs.
Oracle’s goal with GraphPipe is to standardize the process of model deployment regardless of the frameworks utilized in the model creation stage.
On a monthly basis, I will be rounding up key news associated with the Data Science Platforms space for Amalgam Insights. Companies covered will include:
This summer, my Amalgam Insights colleague Hyoun Park and I will be teaming up to address that question. When it comes to data science platforms, there’s no such thing as “one size fits all.” We are writing this landscape because understanding the processes of scaling data science beyond individual experiments and integrating it into your business is difficult. By breaking down the key characteristics of the data science platform market, this landscape will help potential buyers choose the appropriate platform for your organizational needs. We will examine the following questions that serve as key differentiators to determine appropriate data science platform purchasing solutions to figure out which characteristics, functionalities, and policies differentiate platforms supporting introductory data science workflows from those supporting scaled-up enterprise-grade workflows.
Key Stakeholders: Chief Information Officers, Chief Financial Officers, Chief Operating Officers, Chief Digital Officers, Chief Technology Officer, Accounting Directors and Managers, Sales Operations Directors and Managers, Controllers, Finance Directors and Managers, Corporate Planning Directors and Managers Why It Matters: Workday snatched Adaptive Insights away from the public markets only days before IPO, acquiring a proven enterprise planning…
Industry: Data Science Platforms
Key Stakeholders: IT managers, data scientists, data analysts, database administrators, application developers, enterprise statisticians, machine learning directors and managers, current DataScience.com customers, current Oracle customers
Why It Matters: Oracle released a number of AI tools in Q4 2017, but until now, it lacked a data science platform to support complete data science workflows. With this acquisition, Oracle now has an end-to-end platform to manage these workflows and support collaboration among teams of data scientists and business users, and it joins other major enterprise software companies in being able to operationalize data science.
Top Takeaways: Oracle acquired DataScience.com to retain customers with data science needs in-house rather than risk losing their data science-based business to competitors. However, Oracle has not yet not defined a timeline for rolling out the unified data science platform, or its future availability on the Oracle Cloud.
Oracle Acquires DataScience.com
On May 16, 2018, Oracle announced that it had agreed to acquire DataScience.com, an enterprise data science platform that Oracle expects to add to the Oracle Cloud environment. With Oracle’s debut of a number of AI tools last fall, this latest acquisition telegraphs Oracle’s intent to expedite its entrance into the data science platform market by buying its way in.
Oracle is reviewing DataScience.com’s existing product roadmap and will supply guidance in the future, but they mean to provide a single unified data science platform in concert with Oracle Cloud Infrastructure and its existing SaaS and PaaS offerings, empowering customers with a broader suite of machine learning tools and a complete workflow.
On March 27th, Oracle announced availability of the Oracle Autonomous Data Warehouse Cloud, a service that will spin up a data warehouse and provide automated security, high availability, performance tuning, scaling, patching, and administration at a cost guaranteeed to be half of equivalent Amazon Web Services resources through May 2019. Built on Oracle Database 18c, this new service is both a godsend and a warning call for IT.
As Amalgam said last December, Oracle’s push towards what they are calling the “Autonomous Database” and “Autonomous Cloud” is an important step forward in envisioning an new generation of IT where the operational tasks of rules-based administration, monitoring, and iterative performance tuning are handled without direct human intervention. This will allow IT departments to drive more infrastructure into the cloud and reduce the overall Total Cost of Ownership. This is a fundamental change and differs radically from cloud providers such as Amazon and Microsoft that are providing granular services, but are not replacing the management of those services.
Here’s what you should expect
Recommended Reading for: Finance, Sales Operations, Supply Chain Management, IT Management, and Enterprise Strategy Personnel
Companies Mentioned: Anaplan, IBM, SAP, Oracle, Microstrategy, Tableau, DataRobot, TROVE Data, Louis Vuitton, Premji Invest, Salesforce Ventures, Top Tier Capital Partners, Baillie Gifford, Granite Ventures, Industry Ventures, Meritech Capital, Constellation Research, Ventana Research, IDC, Mint Jutras, ISG, Gartner, Apps Run the World, TechVentive
On March 6th and 7th, 2018, Amalgam Insights attended Anaplan Hub 18. Anaplan has been on Amalgam analysts’ radar for several years, as we consider Anaplan’s Hyperblock foundation and ability to serve multi-departmental planning in enterprises without a year or more of setup to be fundamental advantages. As we have covered this company, we have been waiting for Anaplan to reach its breakthrough moment where it takes its place as one of the true market leaders in enterprise applications. It is in this context that we attended Anaplan Hub and judged our interactions with Anaplan executives, customers, and partners.
This report provides updates on Anaplan’s key business metrics, executive insights from an analyst-only panel, keynote and product announcements, a 2018 perspective on customer success stories with Anaplan, and Amalgam’s expectations for Anaplan in 2018 and beyond as both a real-time planning application and a Platform as a Service.
Anaplan Key Business Updates
Blockchain looks to be one of those up and coming technologies that is constantly being talked about. Many of the largest IT companies – IBM, Microsoft, and Oracle to name few – plus a not-for-profit or two are heavily promoting blockchain. Clearly, there is intense interest, much of it fueled by exotic-sounding cryptocurrencies such as Bitcoin and Ethereum. The big question I get asked – and analysts are supposed to be able to answer the big questions – is “What can I use blockchain for?”