Is IBM’s Acquisition of Red Hat the Biggest Acquihire of All Time?

Estimated Reading Time: 11 minutes

Internally, Amalgam Insights has been discussing why IBM chose to acquire Red Hat for $34 billion dollars fairly intensely. Our key questions included:

  • Why would IBM purchase Red Hat when they’re already partners?
  • Why purchase Red Hat when the code is Open Source?
  • Why did IBM offer a whopping $34 billion, $20 billion more than IBM currently has on hand?

As a starting point, we posit that IBM’s biggest challenge is not an inability to understand its business challenges, but a fundamental consulting mindset that starts with the top on down. By this, we mean that IBM is great at identifying and finding solutions on a project-specific basis. For instance, SoftLayer, Weather Company, Bluewolf, and Promontory Financial are all relatively recent acquisitions that made sense and were mostly applauded at the time. But even as IBM makes smart investments, IBM has either forgotten or not learned the modern rules for how to launch, develop, and maintain software businesses. At a time when software is eating everything, this is a fundamental problem that IBM needs to solve.

The real question for IBM is whether IBM can manage itself as a modern software company.

Please register or log into your Free Amalgam Insights Community account to read more.
Log In Register

Tom Petrocelli Provides Context for IBM’s Acquisition of Red Hat

Tom Petrocelli, Amalgam Insights Research Fellow

In light of yesterday’s announcement that IBM is planning to acquire Red Hat for $34 billion, we’d like to share with you some of our recent coverage and mentions of Red Hat to provide context for this gargantuan acquisition.

To learn more about the state of Enterprise Free Open Source Software and the state of DevOps, make sure you continue to follow Tom Petrocelli on this website and his Twitter account.

Data Science Platforms News Roundup, September 2018

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, Cambridge Semantics, Cloudera, Databricks, Dataiku, DataRobot, Datawatch, DominoElastic, H2O.ai, IBM, Immuta, Informatica, KNIME, MathWorks, Microsoft, Oracle, Paxata, RapidMiner, SAP, SAS, Tableau, Talend, Teradata, TIBCO, Trifacta, TROVE.

Please register or log into your Free Amalgam Insights Community account to read more.
Log In Register

Why It Matters that IBM Announced Trust and Transparency Capabilities for AI


Note: This blog is a followup to Amalgam Insights’ visit to the “Change the Game” event held by IBM in New York City.

On September 19th, IBM announced its launch of a portfolio of AI trust and transparency capabilities. This announcement got Amalgam Insight’s attention because of IBM’s relevance and focus in the enterprise AI market throughout this decade.  To understand why IBM’s specific launch matters, take a step back in considering IBM’s considerable role in building out the current state of the enterprise AI market.

IBM AI in Context

Since IBM’s public launch of IBM Watson on Jeopardy! in 2011, IBM has been a market leader in enterprise artificial intelligence and spent billions of dollars in establishing both IBM Watson and AI. This has been a challenging path to travel as IBM has had to balance this market-leading innovation with the financial demands of supporting a company that brought in $107 billion in revenue in 2011 and has since seen this number shrink by almost 30%.

In addition, IBM had to balance its role as an enterprise technology company focused on the world’s largest workloads and IT challenges with launching an emerging product better suited for highly innovative startups and experimental enterprises. And IBM also faced the “cloudification” of enterprise IT in general, where the traditional top-down purchase of multi-million dollar IT portfolios is being replaced by piecemeal and business-driven purchases and consumption of best-in-breed technologies.

Seven years later, the jury is still out on how AI will ultimately end up transforming enterprises. What we do know is that a variety of branches of AI are emerging, including

Please register or log into your Free Amalgam Insights Community account to read more.
Log In Register

Todd Maddox Ph.D.’s Top Four Scientific Observations on HR Tech 2018

HR Tech gets bigger and bigger every year. HR Tech 2018 was no exception. It broke all of the previous records. More importantly, the quality of the offerings, presentations and savvy of the clients continues to grow. I had a great time at HR Tech 2018, and I am already looking forward to 2019. It…

Please register or log into your Free Amalgam Insights Community account to read more.
Log In Register

What Data Science Platform Suits Your Organization’s Needs?

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.

Please register or log into your Free Amalgam Insights Community account to read more.
Log In Register

Lynne Baer: Clarifying Data Science Platforms for Business

Word cloud of data science software and terms

My name is Lynne Baer, and I’ll be covering the world of data science software for Amalgam Insights. I’ll investigate data science platforms and apps to solve the puzzle of getting the right tools to the right people and organizations.

“Data science” is on the tip of every executive’s tongue right now. The idea that new business initiatives (and improvements to existing ones) can be found in the data a company is already collecting is compelling. Perhaps your organization has already dipped its toes in the data discovery and analysis waters – your employees may be managing your company’s data in Informatica, or performing statistical analysis in Statistica, or experimenting with Tableau to transform data into visualizations.

But what is a Data Science Platform? Right now, if you’re looking to buy software for your company to do data science-related tasks, it’s difficult to know which applications will actually suit your needs. Do you already have a data workflow you’d like to build on, or are you looking to the structure of an end-to-end platform to set your data science initiative up for success? How do you coordinate a team of data scientists to take better advantages of existing resources they’ve already created? Do you have coders in-house already who can work with a platform designed for people writing in Python, R, Scala, Julia? Are there more user-friendly tools out there your company can use if you don’t? What do you do if some of your data requires tighter security protocols around it? Or if some of your data models themselves are proprietary and/or confidential?

All of these questions are part and parcel of the big one: How can companies tell what makes a good data science platform for their needs before investing time and money? Are traditional enterprise software vendors like IBM, Microsoft, SAP, SAS dependable in this space? What about companies like Alteryx, H2O.ai, KNIME, RapidMiner? Other popular platforms under consideration should also include Anaconda, Angoss (recently acquired by Datawatch), Domino, Databricks, Dataiku, MapR, Mathworks, Teradata, TIBCO. And then there’s new startups like Sentenai, focused on streaming sensor data, and slightly more established companies like Cloudera looking to expand from their existing offerings.

Over the next several months, I’ll be digging deeply to answer these questions, speaking with vendors, users, and investors in the data science market. I would love to speak with you, and I look forward to continuing this discussion. And if you’ll be at Alteryx Inspire in June, I’ll see you there.

Cloudera Analyst Conference Makes The Case for Analytic & AI Insights at Scale

On April 9th and 10th, Amalgam Insights attended the fifth Cloudera’s Industry Analyst and Influencer Conference (which I’ll self-servingly refer to as the Analyst Conference since I attended as an industry analyst) in Santa Monica. Cloudera sought to make the case that it was evolving beyond the market offerings that it is currently best known for as a Hadoop distribution and commercial data lake in becoming a machine learning and analytics platform. In doing so, Cloudera was extremely self-aware of its need to progress beyond the role of multi-petabyte storage at scale to a machine learning solution.
Cloudera’s Challenges in Enterprise Machine Learning 
Please register or log into your Free Amalgam Insights Community account to read more.
Log In Register

Anaplan States Planning Is Dead, Focuses on the Era of Real-Time Decision


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

Please register or log into your Free Amalgam Insights Community account to read more.
Log In Register