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BigData Analytics
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Data warehouses are an organization’s corporate memory, containing critical information that is the basis for their business management and operations. Organizations then require their data warehouses to be scalable, secure and stable with the ability to optimize storage and retrieval of complex sets of data. Business intelligence systems transform an organization’s ability to convert raw data into information that makes online multidimensional transaction and analytical processing possible.

You can’t pick up a computer industry publication these days without seeing headlines about how “big data” is changing the corporate climate across a broad array of industries. But is big data and related predictive analytics technology only for large enterprises? Definitely not! The recent explosion of digital data has affected businesses of all sizes and has opened opportunities for companies that adopt machine learning technology (of which predictive analytics is a part) to mine intelligence from data assets.

Big data analytics are quickly becoming the new frontier of competitive differentiation. Enterprises must be able to manage large volumes of complex data efficiently and with the best performance in order to be successful. In-Memory BI technology coupled with Visual Insight are an excellent combination for visual exploration of big data.

Solutions Advantages: Big data analytics for any size organization is a vital competitive force by creating new business and drive increased sales. Data-driven companies tend to be better performers with respect to objective measures of operational and financial results. Data-driven decisions tend to be better decisions. Using big data analytics enables decision makers to strategize on the basis of evidence rather than pure intuition. Utilizing corporate data assets more strategically leads to better predictions, and better predictions yield better decisions. .

Solutions Key Benefits:

  • Improved processes and organizations
  • Enhance productivity through reusable service
  • Minimized compliance risk from data security
  • Greater alignment between IT and the business
  • Streamline operations and gain business intelligence
  • Sharpen competitiveness with industry-specific functionality
  • Slash costs and increase profitability

Solutions Competitive Edge: Big data analytics is a decisive competitive asset in many SMB industries and a core element in the effort of all SMBs to improve performance. Performance improvements and competitive advantage arise from classification models that allow decision makers to predict and optimize outcomes. The most effective approach to building a model rarely starts with the data; instead it originates with identifying the business opportunity and determining how the model can improve performance. With big data analytics, decision makers can measure, and hence identify, radically more about their businesses, and directly translate that knowledge into improved decision making, increased performance, and greater opportunities for competitive advantage. But the power of analytics does not remove the need for vision or human instinct. On the contrary, the typical SMB still needs leaders who can spot a great opportunity, understand how a market is developing, think creatively and propose truly novel offerings, and articulate a compelling vision. The time has come to define a pragmatic approach for SMBs to engage predictive analytics that is tightly focused on how to use data to make better decisions.  

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