Expressing a complex world in terms you can understand

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1 Big Data Simplified Expressing a complex world in terms you can understand Information Management has never been easy. Making sure information is modeled, trusted, integrated, and governed to meet the needs of your business has always been an uphill battle. Finding qualified professionals that have expertise in proven techniques and technologies is one of the biggest challenges of successful IT projects. Historically, the impact of scarce Information Management talent was softened by a fairly static learning curve when compared to the world of application development. While software developers chased the latest open-source libraries, professionals that mastered a known set of data modeling tools, relational databases, and ETL platforms could practice their craft for years with only minor disruptions from slight technical improvements and innovations along the way. However, the world has changed, and with these changes come a growing business demand for advanced analytics, thereby introducing new enabling technologies into a once static Information Management landscape. Thus, the traditional challenge of finding proven professionals is compounded by the need for new skills, and an architecture that puts it all into focus. COLLABORATIVE POINT OF VIEW 1

2 Today s Information Management: Changing and complex The landscape of Information Management has changed radically. World events and industry trends have made business and government climates more complex. Industry consolidation produced organizations with increasingly diverse business processes and complicated regulatory environments, which produce and consume massive amounts of information. The tragedies of September 11 th triggered massive information sharing and surveillance initiatives that gave birth to new methods and techniques to analyze and process information. Eventually the internet went social and mobile, and gave rise to a new universe of connected devices which produced forms of information (i.e. the 3Vs), which have challenged conventional platforms for of data analysis. Finally, the financial crisis damaged the economy and left a lot of difficult and complex questions to be answered. With heightened media attention on this increasingly complex world, the business demand for advanced analytics has pressured IT to provide answers and insights into what happened, why it happened, and more importantly what will happen next. Now, enabling technologies to meet this growing demand with answers to these questions have gone mainstream, and the business need for hard-to-find skills has reached critical mass (for more on this topic, please see our webinar on Test Driving Big Data 1 and our pointof-view on taking IM off of cruise control 2 ). C 2 for Big Data: Designed for a complex world Conventional architectures for Information Management must adapt in this changing environment. Collaborative s C 2 for Big Data is designed to simplify the relevant aspects of Big Data, allowing organizations to associate their needs to the promising capabilities available in this new landscape. Focused on giving organizations a business advantage, C 2 for Big Data allows you to climb the Big Data learning curve and meet the growing business demand for analytics by dissecting the disruptive world of Big Data into four main actions. Figure 1: Big data technology timeline 2

3 Connect the old and new worlds of Information Management using proven methods for integrating data-at-rest and data-in-flight. Crunch structured/unstructured information using best-in-class processing and modeling techniques in Data Science. Morph this data into business-centric analytics and visualizations that resonate with the business. Execute business applications and services that provide business insights drawn from complex data sources. The actions above represent paths to clear, definable subject areas that make sense in a changing Information Management landscape which has been blurred by the hype of Big Data. Bear in mind that there is no one technology to deliver on these capabilities. For instance, there are several mechanisms to connect to the vast array of information available on social media sites. There are also multiple programming languages that are capable of machine learning, but some are limited by the algorithms you can implement. Thus if you need neural networks, you d find primitive groundwork in today s version of Mahout, but more complete support in Python. Confused on what neural networks are or whether you need them? Don t worry. Referring back to the early days of data quality and MDM, you probably didn t know if you needed probabilistic or deterministic matching or whether the Jaro distance algorithm would produce the optimal match results. Rather, you needed skilled professionals that can present the capabilities of advanced matching in simple terms, with the skills needed to implement the right mix of algorithms until you have a stable and trained operational model. The same is true in today s world of Big Data, and Collaborative s C 2 provides a simple expression of Big Data capabilities, backed by proven professionals skilled in the art and science of real world applications and experience. Figure 2: The C 2 business advantage 3

4 Where to begin Collaborative has proven services, skills, and accelerators for all aspects of Big Data. Collaborative can show you how to connect information from Social Media, the Internet-of-Things, customer surveys, or dormant archives into resources that are ready to be refined and aligned to existing, trusted sources of information. Our data scientists can crunch raw connected information using a combination of Natural language processing (NLP), machine learning, and modeling methods to classify, cluster, and dig for hidden insights. We also have expertise in analytics and advanced visualization to allow the business to morph this processed information into answers and visualizations that tackle essential analytical questions: what happened, why it happened, and what will happen next. Finally, Collaborative s ready-made dashboards (e.g. sentiment analysis) and M3 architecture for services allow you to execute by building standalone apps or contextualized services that allow the business to comprehend the salient analytics and insights of an increasingly complex world. References 1. Webcast_na_lgna_na_na_wcl 2. taking-information-management-off-cruise-control- POV.IM.108.pdf 4

5 Dan Sandler is a Director of Information Management for Collaborative Consulting. As a Senior Data Architect with over 16 years of experience, Dan specializes in defining data integration, data warehousing, and MDM solutions across a variety of industries. He is also responsible for Collaborative Consulting s Big Data services. Dan earned a BA in Economics from Trinity College and a MBA from Bentley University. Collaborative Consulting is a leading information technology services firm dedicated to helping our clients achieve business advantage through the use of strategy and technology. We deliver a comprehensive set of solutions across multiple industries, with a focus on business process and program management, information management, software solutions, and software performance and quality. We also have a set of offerings specific to the life sciences and financial services industries. Our unique model offers both onsite management and IT consulting as well as U.S.-based remote solution delivery. To learn more about Collaborative, please visit our website at us at collaborative.com, or contact us at Copyright 2014 Collaborative Consulting, LLC. All rights reserved. This product is protected by U.S. and international copyright and intellectual property laws. POV

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