<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gopalakrishna Palem</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Formulating an Executive Strategy for Big Data Analytics</style></title><secondary-title><style face="normal" font="default" size="100%">Technology Innovation Management Review</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">big data</style></keyword><keyword><style  face="normal" font="default" size="100%">business vision</style></keyword><keyword><style  face="normal" font="default" size="100%">executive strategy</style></keyword><keyword><style  face="normal" font="default" size="100%">IT entrepreneurship</style></keyword><keyword><style  face="normal" font="default" size="100%">predictive analytics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://timreview.ca/article/773</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Talent First Network</style></publisher><pub-location><style face="normal" font="default" size="100%">Ottawa</style></pub-location><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">25-34</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The recent surge in big data technologies has left many executives, both of well-established organizations and emerging startups, wondering how best to harness big data. In particular, the analytics aspect of big data is enticing for both information technology (IT) service providers and non-IT firms because of its potential for high returns on investment, which have been heavily publicized, if not clearly demonstrated, by multiple whitepapers, webinars, and research surveys. Although executives may clearly perceive the benefits of big data analytics to their organizations, the path to the goal is not as clear or easy as it looks. And, it is not just the established organizations that have this challenge; even startups trying to take advantage of this big data analytics opportunity are facing the same problem of lack of clarity on what to do or how to formulate an executive strategy. This article is primarily for executives who are looking for help in formulating a strategy for achieving success with big data analytics in their operations. It provides guidelines to them plan an organization's short-term and long-term goals, and presents a strategy tool, known as the delta model, to develop a customer-centric approach to success with big data analytics.</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">
Gopalakrishna Palem is a Corporate Technology Strategist specialized in distributed computing technologies and advanced predictive analytics solutions. During his 12-year tenure at Microsoft and Oracle, he helped many customers build their executive strategy for various technology initiatives, driving the brand-name promotions and improved revenue targets. He offers consultations for C-level executives in technology management strategy and is actively engaged in guiding researchers and entrepreneurs in knowledge modelling systems, algorithmic information theory, and systems control and automata. He can be reached at &lt;a href=&quot;http://gopalakrishna.palem.in/ &quot; target=&quot;_blank&quot;&gt;gopalakrishna.palem.in&lt;/a&gt; </style></custom1></record></records></xml>