I recently attended SAS Institute’s analyst relations conference. There the company provided updates on its financial performance and its Viya platform and a glimpse into some of its future plans.
Topics: business intelligence, Data Science, Internet of Things, Data Integration, Data Governance, Data Preparation, Information Optimization, Machine Learning Digital Technology, Big Data, Machine Learning and Cognitive Computing, Mobile Technology, Analytics, Cloud Computing, Collaboration
Ventana Research analysts recently published our research agendas for 2017. As we put together these plans we think about the forces that are shaping the markets that we cover and then craft agendas that study these issues to provide insights for our community. I’ve been working in the business intelligence (BI) and analytics market for nearly 25 years, and throughout that time the industry has been trying to make analytics useful to increasingly wider audiences. That focus continues to today. Better search and presentation methods, including visual discovery and natural-language processing, are promising ways to engage more users. We also see organizations supporting their users in specific functional roles with relevant and accessible analytics. My colleagues examine these issues as part of their agendas in the Office of Finance, Sales, Marketing, Customer Experience, Operations and Supply Chain, and Human Capital Management. While their agendas include analytics within specific domains, my own research focuses on a range of analytics issues across domains including cloud computing, mobility, collaboration, data science and the Internet of Things.
IBM recently held its inaugural World of Watson event. Formerly known as IBM Insight, and prior to that IBM Information on Demand, the annual event, attended by 17,000 people this year, showcases IBM’s data and analytics and the broader IBM efforts in cognitive computing. The theme for the event, as you might guess, was the Watson family of cognitive computing products. I, for one, was glad to spend more time getting to know the Watson product line, and I’d like to share some of my observations from the event.
I recently attended Oracle OpenWorld for the first time in several years. The message at this year’s event was clear: Oracle is all in on the cloud. I had heard the message, but I didn’t get the full impact until I arrived at the Moscone Center in San Francisco. All signage at the event contained the word “cloud,” and Oracle issued 18 press releases in conjunction with OpenWorld related to cloud computing. I also found out that Oracle has its own definition of “cloud.”
Teradata recently held its annual Partners conference, at which gather several thousand customers and partners from around the world. This was the first Partners event since Vic Lund was appointed president and CEO in May. Year on year, Teradata’s revenues are down about 5 percent, which likely prompted some changes at the company. Over the past few years Teradata made several technology acquisitions and perhaps spread its resources too thin. At the event, Lund committed the company to a focus on customers, which was a significant part of Teradata’s success in the past. This commitment was well received by customers I spoke with at the event.
Predictive analytics is a rewarding yet challenging subject. In our benchmark research on next-generation predictive analytics at least half the participants reported that predictive analytics allows them to achieve competitive advantage (57%) and create new revenue opportunities (50%). Yet even more participants said that users of predictive analytics don’t have enough skills training to produce their own analyses (79%) and don’t understand the mathematics involved (66%). (In the term “predictive analytics” I include all types of data science, not just one particular type of analysis.)
Qlik helped pioneer the visual discovery market with its QlikView product. In some respects, Qlik and its competitors also spawned the self-service trend rippling through the analytics market today. Their aim was to enable business users to perform analytics for themselves rather than building a product with the perfect set of features for IT. After establishing success with end users the company began to address more of the concerns of IT, eventually creating a robust enterprise-grade analytics platform. This approach has worked for Qlik, driving growth that led to an initial public offering in 2010. The company now generates more than half a billion dollars in revenue annually, making it one of the largest independent analytics vendors. Of which based on their company and products was rated a Hot Vendor in our 2015 Value Index on Analytics and Business Intelligence and one of the highest ranked in usability.
Throughout the course of our research in 2016, we’ll be exploring ways in which organizations can maximize the value of their data. Ventana Research believes that analytics is the engine and data is the fuel to power better business decisions. Several themes emerged from our benchmark research on incorporating data and analytics into organizational processes, and we will follow them in our 2016 Business Analytics Research Agenda:
Topics: Analytics, Big Data, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Information Applications, Information Management, Operational Intelligence, Predictive Analytics
I want to share my observations from the recent annual SAS analyst briefing. SAS is a huge software company with a unique culture and a history of success. Being privately held SAS is not required to make the same financial disclosures as publicly held organizations, it released enough information to suggest another successful year, with more than $2.7 billion in revenue and 10 percent growth in its core analytics and data management businesses. Smaller segments showed even higher growth rates. With only selective information disclosed, it’s hard to dissect the numbers to spot specific areas of weakness, but the top-line figures suggest SAS is in good health.
In our definition, information management encompasses the acquisition, organization, dissemination and use of information by organizations to create and enhance business value. Effective information management ensures optimal access, relevance, timeliness, quality and security of this data with the aim to improve organizational performance. This goal is not easily met, especially as organizations acquire ever more data at an ever faster pace. In our business analytics benchmark research of more than 2,600 organizations, almost half (45%) have to integrate six or more types of data in their analyses. More than two-thirds reported that they spend more time preparing data than analyzing it. To assist in dealing with these sorts of issues and others, we’ve laid out an ambitious information management research agenda for 2012.
Topics: Analytics, Business Analytics, Business Intelligence, Cloud Computing, Complex Event Processing, Data Governance, Data Integration, Data Quality, Information Applications, Information Life Cycle Management, Information Management, Master Data Management, Operational Intelligence, Social Media, IT Performance Management (ITPM)