I recently attended Teradata’s Third-Party Influencers Meeting (Twitter Hashtag #TD3PI) in Las Vegas where the company updated industry analysts and consultants on upcoming product plans and the status of two product lines it added via acquisition in the past year. Randy Lea, Teradata’s VP of product management and marketing, provided a company overview recapping highlights and defining the corporate strategy building on its work in 2010 that my colleague assessed. Teradata focuses on three markets: its core business of data warehousing, which it identified as a $27 billion market, the $15 billion business applications market represented by its Aprimo acquisition, and the big-data analytics market, a $2 billion market addressed in part by its Aster Data acquisition. I mention Teradata’s estimates of market size as they may indicate the emphasis and investment the company will make in each segment. Lea referred to Teradata’s independence from NCR, for almost four years, as a good thing. Independence, he said, has allowed Teradata to focus, to release products more frequently and to acquire companies that enhance their market position. Judging by the performance of its stock (NYSE: TDC), the financial markets seem to agree independence has been good – even with the recent market downturn its stock is up 75% in the last year.
Topics: Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Workforce Performance
SnapLogic, a cloud-based data integration vendor, has extended its product linewith new data quality capabilities. This is worth comment because SnapLogic sits at the intersection of two recent trends in information management.
Topics: Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, Information Management, Workforce Performance
Cloudera is riding the wave of big data. I first learned about the company while working at Vertica, one of Cloudera’s partners. Customers that managed large amounts of structured relational data also needed to process large amounts of semistructured data such as the type found in web logs and application logs. The emerging channel of social media provided another source of data lacking the structure that would lend itself to analysis in a relational database. Other organizations needed to perform calculations and analyses that were difficult to express in SQL. Seeing this market Cloudera recognized earlier than others an opportunity to leverage the Apache Hadoop project; it has been offering the Cloudera Distribution for Hadoop (CDH) since early 2009.
Topics: Big Data, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Business Analytics, Business Intelligence, Business Performance, CDH3, Cloudera, Customer & Contact Center, Information Management, Strata+Hadoop
I recently attended IBM’s analyst summit on business analytics. Since last year’s event was largely a preview of Cognos 10, which was several years in the making, I wondered what this year’s event would be about. IBM focused much of the attention on predictive analytics, strengthened by its acquisition of SPSS. My colleague Robert Kugel covered another theme from the event in his post on Cognos Planning.
Topics: Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, Operational Intelligence, Workforce Performance
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)
In various forms, business intelligence (BI) – as queries, reporting, dashboards and online analytical processing (OLAP) – is being used increasingly widely. And as basic BI capabilities spread to more organizations, innovative ones increasingly are exploring how to take advantage of the next step in the strategic use of BI: predictive analytics. The trend in Web searches for the phrase “predictive analytics” gives one indication of the rise in interest in this area. From 2004 through 2008, the number of Web search was relatively steady. Beginning in 2009, the number of searches rose significantly and has continued to rise.
Topics: Predictive Analytics, Predixion, R, Revolution Analtyics, Sales, Sales Performance, SAS, Social Media, Supply Chain Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Business Technology, CIO, Cloud Computing, Customer & Contact Center, Financial Performance, IBM SPSS, Information Builders, Information Technology, KXEN, Netezza, Oracle, Workforce Performance