[/caption] Businesses will need trained analysts and a variety of new modeling technologies to handle a rising flood of data, according to an upcoming analyst report. “While newer technologies are in play for capturing and massaging big data, farther down the line, the need for business analyst analytics is greater than ever,” Neil Raden, a vice president and principal analyst at Constellation Research, wrote in the report’s executive summary issued June 26. “In the past, the B.I. calculus more or less ended with informing people. Today, it is action supported by deep insight that is demanded.” Excel, he wrote, doesn’t have the internal capabilities for interacting with the models informed by Big Data. That’s a sea change from past years, when Excel eclipsed the use of modeling for many data-mining functions within most companies. Of the six “major B.I. vendors of the late 90s through today,” he added, roughly 20 percent of revenue derived from modeling tools, with the rest “strictly read-only from data warehouses and marts.” (Those six companies are BusinessObjects/SAP, Cognos/IBM, SAS, Hyperion/Oracle, Microsoft and Microstrategy.) Indeed, he sees software as a relatively paltry share of the market: “The lion’s share of revenue in the big data market will continue to be hardware and services, not software.” That is, “unless you consider the application of existing technologies, especially database and data integration software, as part of big data.” A variety of IT vendors, of course, have been rushing to fill the gap in technology. Squeezed between the growing data demands of organizations, and a rapidly escalating number of tools for analyzing that data, IT administrators, highly trained data analysts and other pros could all find themselves quickly overloaded by demand. The solution, at least according to some analysts, is B.I. tools designed for use by regular employees. Forrester analyst Boris Evelson recommended in a recent note that business workers carry out roughly 80 percent of all an organization’s B.I. requirements, leaving IT pros to handle the other 20 percent. That being said, he also cautioned that “complex, mission-critical, enterprise-wide B.I. applications” should remain in the hands of the highly trained. In that same research note, he added that vital self-service B.I. capabilities include automodeling of raw data, search-like GUI (graphical user interface), application sandboxes, and exploration and discovery on raw data. Image: Sam.C/Shutterstock.com Big Data Demands Analysts, New Tech: Report
[caption id="attachment_2045" align="aligncenter" width="400" caption="This image represents the rising amount of data set to drive your IT department into a new world of frustration."] [/caption] Businesses will need trained analysts and a variety of new modeling technologies to handle a rising flood of data, according to an upcoming analyst report. “While newer technologies are in play for capturing and massaging big data, farther down the line, the need for business analyst analytics is greater than ever,” Neil Raden, a vice president and principal analyst at Constellation Research, wrote in the report’s executive summary issued June 26. “In the past, the B.I. calculus more or less ended with informing people. Today, it is action supported by deep insight that is demanded.” Excel, he wrote, doesn’t have the internal capabilities for interacting with the models informed by Big Data. That’s a sea change from past years, when Excel eclipsed the use of modeling for many data-mining functions within most companies. Of the six “major B.I. vendors of the late 90s through today,” he added, roughly 20 percent of revenue derived from modeling tools, with the rest “strictly read-only from data warehouses and marts.” (Those six companies are BusinessObjects/SAP, Cognos/IBM, SAS, Hyperion/Oracle, Microsoft and Microstrategy.) Indeed, he sees software as a relatively paltry share of the market: “The lion’s share of revenue in the big data market will continue to be hardware and services, not software.” That is, “unless you consider the application of existing technologies, especially database and data integration software, as part of big data.” A variety of IT vendors, of course, have been rushing to fill the gap in technology. Squeezed between the growing data demands of organizations, and a rapidly escalating number of tools for analyzing that data, IT administrators, highly trained data analysts and other pros could all find themselves quickly overloaded by demand. The solution, at least according to some analysts, is B.I. tools designed for use by regular employees. Forrester analyst Boris Evelson recommended in a recent note that business workers carry out roughly 80 percent of all an organization’s B.I. requirements, leaving IT pros to handle the other 20 percent. That being said, he also cautioned that “complex, mission-critical, enterprise-wide B.I. applications” should remain in the hands of the highly trained. In that same research note, he added that vital self-service B.I. capabilities include automodeling of raw data, search-like GUI (graphical user interface), application sandboxes, and exploration and discovery on raw data. Image: Sam.C/Shutterstock.com
[/caption] Businesses will need trained analysts and a variety of new modeling technologies to handle a rising flood of data, according to an upcoming analyst report. “While newer technologies are in play for capturing and massaging big data, farther down the line, the need for business analyst analytics is greater than ever,” Neil Raden, a vice president and principal analyst at Constellation Research, wrote in the report’s executive summary issued June 26. “In the past, the B.I. calculus more or less ended with informing people. Today, it is action supported by deep insight that is demanded.” Excel, he wrote, doesn’t have the internal capabilities for interacting with the models informed by Big Data. That’s a sea change from past years, when Excel eclipsed the use of modeling for many data-mining functions within most companies. Of the six “major B.I. vendors of the late 90s through today,” he added, roughly 20 percent of revenue derived from modeling tools, with the rest “strictly read-only from data warehouses and marts.” (Those six companies are BusinessObjects/SAP, Cognos/IBM, SAS, Hyperion/Oracle, Microsoft and Microstrategy.) Indeed, he sees software as a relatively paltry share of the market: “The lion’s share of revenue in the big data market will continue to be hardware and services, not software.” That is, “unless you consider the application of existing technologies, especially database and data integration software, as part of big data.” A variety of IT vendors, of course, have been rushing to fill the gap in technology. Squeezed between the growing data demands of organizations, and a rapidly escalating number of tools for analyzing that data, IT administrators, highly trained data analysts and other pros could all find themselves quickly overloaded by demand. The solution, at least according to some analysts, is B.I. tools designed for use by regular employees. Forrester analyst Boris Evelson recommended in a recent note that business workers carry out roughly 80 percent of all an organization’s B.I. requirements, leaving IT pros to handle the other 20 percent. That being said, he also cautioned that “complex, mission-critical, enterprise-wide B.I. applications” should remain in the hands of the highly trained. In that same research note, he added that vital self-service B.I. capabilities include automodeling of raw data, search-like GUI (graphical user interface), application sandboxes, and exploration and discovery on raw data. Image: Sam.C/Shutterstock.com