David Menninger's Analyst Perspectives

IBM Brings Breadth and Depth to Analytics

Posted by David Menninger on Feb 13, 2019 6:00:00 AM

I am happy to share some insights about IBM drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated IBM and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

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Topics: Data Science, Mobile Technology, Analytics, Business Intelligence, Cloud Computing, Collaboration, Digital Technology

MicroStrategy Battles for Top Spot in Analytics and BI

Posted by David Menninger on Feb 8, 2019 6:00:00 AM

I am happy to offer some insights on MicroStrategy drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated MicroStrategy and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

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Topics: Mobile Technology, Analytics, Business Intelligence, Cloud Computing, Collaboration, Digital Technology

Consolidation around Cognos 11.1 and other news from IBM Analytics University

Posted by David Menninger on Dec 3, 2018 7:00:00 AM

IBM's Analytics University (held in both Miami and Stockholm) brought about some large changes. Big announcements this year included a consolidation of IBM's Watson Analytics into Cognos 11.1, helping provide some clarity to their analytics offerings, along with new visualizations and better data preparation. This also includes a new conversational assistant to help generate narrative explanations of displays and interactive queries. For the full breakdown of IBM's Analytics University 2018, and my analysis of all the largest announcements, watch my latest hot take.

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Topics: Big Data, Analytics, Business Intelligence, Data Preparation, AI, natural language processing

The Market of Data at Strata

Posted by David Menninger on Oct 5, 2018 11:31:56 AM

In 2017 Strata + Hadoop World was changed to the Strata Data Conference. As I pointed out in my coverage of last year’s event, the focus was largely on machine learning and artificial intelligence (AI). That theme continued this year, but my impression of the event was of a community looking to get value out of data regardless of the technology being used to manage that data. The change was subtle: The location was the same; the exhibitors were largely the same; attendance was similar this year and last. But there was no particular vendor or technology dominating the event.

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Topics: Big Data, Data Science, Machine Learning, Analytics, Business Intelligence, Data Governance, Data Integration, Data Preparation, Information Optimization, Digital Technology, Machine Learning and Cognitive Computing

From Analytics to Action Requires Collaboration

Posted by David Menninger on Sep 20, 2018 8:35:29 AM

All too often, software vendors view analytics as the end rather than the beginning of a process. I’m reminded of some of the advanced math classes I’ve taken in which the teaching process focused on a few key aspects of a mathematical proof or solution, leaving the rest of the exercise to be worked out by the students. In other contexts, you may hear people say the numbers speak for themselves.

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Topics: Data Science, Machine Learning, Analytics, Business Intelligence, Collaboration, Data Governance, Information Optimization, Digital Technology, collaboration for business

Research Agenda Explores Evolving World of Analytics in 2018

Posted by David Menninger on Feb 12, 2018 5:17:18 AM

We at Ventana Research recently published our research agendas for 2018. Analytics and business intelligence are evolving and so is our research on their use across practice areas. Earlier research has shown that analytics can deliver significant value to organizations; for example, our predictive analytics research shows that 57 percent of organizations reported achieving a competitive advantage and half created new revenue opportunities with predictive analytics. Waves of investment in self-service analytics have propelled the market for analytics tools, significantly empowering line-of-business organizations to create their own analytics and set their own analytic priorities. But organizations are also beginning to recognize some of the limitations of current analytics implementations – for self-service, for example. Our Data Preparation Benchmark Research reveals that fewer than half (42%) of organizations are comfortable allowing business users to work with data not prepared by IT. Our research this year will continue to explore both the successes and challenges organizations face as they continue to use analytics and BI.

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Topics: Machine Learning, Analytics, Business Intelligence, Collaboration, Internet of Things, IOT, Artificial intelligence, natural language processing, Natural Language Query

Natural Language Generation Broadens the Reach of Analytics and BI

Posted by David Menninger on Sep 1, 2017 10:09:08 AM

Natural language generation (NLG), the process of generating text or narratives based on a set of data values, can reach a broader audience. NLG narratives can be used for a variety of purposes, but in this perspective I focus on how NLG can be used to enhance business intelligence (BI) processes. In the case of BI, NLG can be used to explain what has happened and why it is happening, and even what actions to take. The NLG narratives can be understood by a broader range of business users than the tables and charts of data that are the typical output of most BI applications or analytics tools.

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Topics: Machine Learning, Natural Language, Analytics, Business Intelligence, NLG

Choose Your IoT Technologies Wisely

Posted by David Menninger on Jul 3, 2017 5:33:07 AM

This is my second analyst perspective based on our IoT Benchmark Research. In the first, I discussed the business focus of IoT applications and some of the challenges organizations are facing. Now I’ll share some of the findings about technologies used in IoT applications and the impact those technologies appear to have on the success of users’ projects.

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Topics: Big Data, Analytics, Business Intelligence, IOT, NoSQL

The Year of Machine Learning

Posted by David Menninger on Jun 1, 2017 10:26:20 AM

This year various types of organizations are embracing machine learning like it is going out of style – or maybe it would be better to say coming into style. And now with a little investigation on LinkedIn finds over half million professionals with machine learning in their job title. Machine learning is the application of specific data science algorithms that become more accurate as the system records more outcomes and processes more data. This improvement is referred to as “learning,” hence the name. There are good reasons machine learning is growing so rapidly, but there are pitfalls to avoid as well.

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Topics: Big Data, Data Science, Analytics, Business Intelligence, Cloud Computing, Machine Learning and Cognitive Computing, Machine Learning Digital Technology

Informatica Asserts Its Commitment to the Cloud and Machine Learning

Posted by David Menninger on May 27, 2017 12:19:53 AM

Informatica reintroduced itself to the world at its recent customer conference, Informatica World, in San Francisco. The company took advantage of the event to showcase its new branding in an effort to change the way customers think about the company. Informatica has been providing information services in the cloud for more than a decade. Even though cloud revenue comprises a minority of Informatica’s business, in absolute terms, the revenue is significant, and company executives want the public to recognize Informatica as a leader in cloud-based data management services for enterprises. Presenters also made notable product announcements, discussed below, including the application of machine learning to the data management process.

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Topics: Big Data, Data Science, Analytics, Business Intelligence, Cloud Computing, Data Governance, Data Integration, Data Preparation, Information Optimization, Machine Learning and Cognitive Computing, Machine Learning Digital Technology