Some followers of Ventana Research may recall my work here several years ago. Here and elsewhere I have spent most of my career in the data and analytics markets matching user requirements with technologies to meet those needs. I’m happy to be returning to Ventana Research to resume investigating ways in which organizations can make the most of their data to improve their business processes; for a first look, please see our 2016 research agenda on Big Data and Information Optimization. I relish the opportunity to conduct primary market research in the form of Ventana’s well-known benchmark research and to help end users and vendors apply the information collected in those studies.
Topics: Big Data, Predictive Analytics, Analytics, Business Analytics, Business Intelligence, Information Management, Internet of Things, Operational Intelligence, Uncategorized, Unicorns, IT Performance Management (ITPM)
As a technology, predictive analytics has existed for years, but adoption has not been widespread among businesses. In our recent benchmark research on business analytics among more than 2,600 organizations, predictive analytics ranked only 10th among technologies they use to generate analytics, and only one in eight of those companies use it. Predictive analytics has been costly to acquire, and while enterprises in a few vertical industries and specific lines of business have been willing to invest large sums in it, they constitute only a fraction of the organizations that could benefit from them. Ventana Research has just completed a benchmark research project to learn about how the organizations that have adopted predictive analytics are using it and to acquire real-world information about their levels of maturity, trends and best practices. In this post I want to share some of the key findings from our research.
Topics: Data Scientist, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Analytics, Business Analytics, Business Intelligence, Customer & Contact Center, Workforce Performance, IT Performance Management (ITPM)
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: Data Quality, Master Data Management, Social Media, Analytics, Business Analytics, Business Intelligence, Cloud Computing, Complex Event Processing, Data Governance, Data Integration, Information Applications, Information Life Cycle Management, Information Management, Operational Intelligence, IT Performance Management (ITPM)
About 30 years ago, perhaps on this very day, I was sitting in front of an Apple II working on a VisiCalc spreadsheet. At the time, I don’t think I even knew who Steve Jobs was. I wasn’t in the software industry yet. I was working for a public accounting firm. The Apple II sat in a corner of the office “typing pool.” For those of you who don’t know what a typing pool was, there was no swimming involved – it was a group of full-time employees with dedicated equipment who did all the typing and word processing tasks of the office.
Topics: Mobile, Sales Performance, Social Media, Supply Chain Performance, Sustainability, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Customer & Contact Center, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Location Intelligence, Operational Intelligence, Visualization, IT Performance Management (ITPM)
Splunk may be one of the biggest software companies you’ve never heard of. I’ve been following the seven-year-old company for over six months now and recently attended its second annual user conference. Splunk focuses on analyzing large volumes of machine-generated data in underlying applications and systems, which includes application and system logs, network traffic, sensor data, click streams and other loosely structured information sources. Many of these “big data” sources are the same sources analyzed with Hadoop, according to our recently published benchmark research. However, Splunk takes a different approach that focuses on performing simple analyses on this data in real time rather than the batch-based advanced analytics we see as the most common use for Hadoop.
Topics: Big Data, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Machine data, Operational Intelligence, IT Performance Management (ITPM)
Last week I attended the IBM Big Data Symposium at the Watson Research Center in Yorktown Heights, N.Y. The event was held in the auditorium where the recent Jeopardy shows featuring the computer called Watson took place and which still features the set used for the show – a fitting environment for IBM to put on another sort of “show” involving fast processing of lots of data. The same technology featured prominently in IBM’s big-data message, and the event was an orchestrated presentation more like a TV show than a news conference. Although it announced very little news at the event, IBM did make one very important statement: The company will not produce its own distribution of Hadoop, the open source distributed computing technology that enables organizations to process very large amounts of data quickly. Instead it will rely on and throw its weight behind the Apache Hadoop project – a stark contrast to EMC’s decision to do exactly that, announced earlier in the week. As an indication of IBM’s approach, Anant Jhingran, vice president and CTO for information management, commented, “We have got to avoid forking. It’s a death knell for emerging capabilities.”
Topics: Big Data, EMC, Analytics, Business Analytics, Business Intelligence, Cloud Computing, Cloudera, Customer & Contact Center, Greenplum, IBM, Information Applications, Information Management, InfoSphere, Location Intelligence, Operational Intelligence, IT Performance Management (ITPM), Strata+Hadoop
As part of our largest-ever research study on business analytics, which surveyed more than 2,600 organizations covering the maturity and competency of business, IT and vertical industries, we looked at how IT is applying analytics to support their own business activities. One of the things we found is that, charged with enabling business units to use information systems as effectively as possible, the IT department, like the shoemaker’s barefoot children in the old tale, typically stands last in line for resources to manage its own performance. In trying to understand and tune the collection of networking and operating systems, middleware and applications an enterprise needs to operate, IT professionals usually have to make do with small sets of historical data stored in spreadsheets and data warehouses and marts that are not as well managed as the systems they maintain to support the business. In most cases IT cannot apply the same level of analytics to its own operations that it provides to business units. This also has effects beyond IT itself: To the extent that the result is subpar performance of its core information systems, the business will suffer.
Topics: Predictive Analytics, Analytics, Business Analytics, Business Intelligence, Business Performance, Information Applications, Information Management, Information Technology, IT Analytics, IT Service Management, ITIL, ITSM, IT Performance Management (ITPM)
The information management (IM) technology market is undergoing a revolution similar to the one in the business intelligence (BI) market. We define information management as the acquisition, organization, control and use of information to create and enhance business value. It is a necessary ingredient of successful BI implementations, and while some vendors such as IBM, Information Builders, Pentaho and SAP are in addition integrating their BI and IM offerings, each discipline involves different aspects of the use of information and will require it sometimes integrated and sometimes separate.
Topics: Data Quality, Social Media, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Technology, CIO, Complex Event Processing, Data Governance, Data Integration, Information Management, Information Technology, Operational Intelligence, IT Performance Management (ITPM)
The business intelligence (BI) technology market is undergoing a revolution. I’ve been working in this segment for 20 years, and it is and has been an exciting market in which to work, but its dynamic nature can be daunting to organizations trying to evaluate, purchase and deploy BI to improve their business processes. And despite the advances our benchmark research shows high levels of dissatisfaction with and immaturity in BI capabilities within organizations.
Topics: Sales Performance, Social Media, Supply Chain Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Business Technology, CIO, Cloud Computing, Collaboration, Customer & Contact Center, Enterprise Software, Financial Performance, Information Technology, Mobility, Operational Intelligence, IT Performance Management (ITPM)
I recently attended SAS Institute’s annual analyst conference. My colleague covered the multibillion-dollar company’s strategy and the event. Now I want to look into some of the details of SAS’s products for business analytics and how they are supported with business intelligence (BI), and information management. Although SAS is not a publicly traded company and therefore is not required to make the financial disclosures that others are, the company revealed numerous financial statistics. Business intelligence represents over $200 million in license revenue to SAS. That’s a significant figure, larger than publicly traded BI vendors QlikTech (NASDAQ: QLIK) and Actuate (NASDAQ: BIRT) have and smaller than but still in the same order of magnitude as MicroStrategy (NASDAQ: MSTR) and Information Builders. These figures are consistent with results in our benchmark research on business intelligence and performance management: 18% of our research respondents reported using SAS products, which places it in the middle of the pack.
Topics: SAS, Social Media, Analytics, Business Intelligence, Business Performance, Business Technology, CIO, Collaboration, Enterprise Software, Information Management, Information Technology, Mobility, Operational Intelligence, IT Performance Management (ITPM)