Many organizations, with varying mission sets and strategic objectives, face the challenge of optimizing the use of large data sets.
Data is information, and information is power (as the saying goes). However, having possession and control of a database, most likely compiled from disparate sources, does not lead easily to the efficient use and effective application of information to enrich your business and decision lifecycle. Companies, particularly the subject matter experts, need to clean and code the data in order for information to acquire meaning from which thought-leaders and stakeholders alike can successfully extract meaning. Moreover, the process of establishing Standard Operating Procedures (SOPs) and maintaining a routine methodology will enable users to not only manipulate information in a usable model but also empower decision makers to move large data applications to the market or operating space.
The concept of data-as-a-service is essential to maximizing the meaning of the information to both companies and clients. For years, organizations have processed data by purchasing mailing lists or a data bank. Now, with the focus on “big data,” stakeholders are focusing on social networking data and realizing its value for research and analysis. For example, by harnessing the potential inherent in the data streams through the integration of big data into a company’s sales lifecycle, program managers and decision makers are able to identify a previously-untapped line of prospective customers.
One challenge understood across diverse communities it is difficult to understand how to leverage big data while managing the waves of social networks. Doug Cutting, the originator of Hadoop, performs massive searches on these data sets and indexes it for queries. Hadoop is a next generation technology. However, aside from dealing with effectively managing large data sets, most IT departments still face additional challenges with OLAP cubes and writing Structured Query Language (SQL) scripts daily to run reports. Lastly, overcoming potential or existing barriers in the the way in which generations understand the use and application of big data is a challenge for managers. Although users manipulate data in Microsoft Excel (MS Excel), for example, unwillingness to perform key analysis according to SOPs hinders or prevents a department’s ability to provide accurate and timely reporting.
Microsoft Corporation recognizes these challenges, and is continuing to work on Project Isotope to incorporate Hadoop cloud software with Windows Azure OS. In unique fashion, Microsoft plans to integrate MS Excel and a PowerPivot add-in, which will significantly enable managers and users to employ an Excel interface to manipulate and analyze big data. Additionally, utilizing Bing‘s search tool and Microsoft’s propensity for API integration, the combination presents a high-value match.
Team Praescient will be watching the NYC Structure Data Conference in March. Conference speakers and panelists will explore the technical and business opportunities spurred by growth in big data, including storage needs, data analysis, and the uncovering of new revenue opportunities. Of particular interest, Praescient will pay attention to how industries are Putting Big Data to Work in order to use big data to create a business of information and deliver new products to customers.