One of the most distinct characteristic of the modern Enterprise Nowadays is the Big Data – information of extreme size, diversity and complexity – is everywhere. This disruptive phenomenon is destined to help organizations drive innovation by gaining new and faster insight into their customers.

Enterprise Big Data

Key Challenges in Big Data

Big data forces us to wrestle with three key strategic and operational challenges:

  • Information Strategy: We need to harness the power of information assets. Big data is causing enterprises to find new ways to leverage information sources to drive growth. 
  • Data Analytics: We need to draw more insight from our big data analytics or large and complex datasets. We need to predict future customer behaviors, trends and outcomes. 
  • Enterprise Information Management: Information is everywhere – volume, variety, velocity – and it keeps growing. We need to manage access to growing extreme information management requirements and drive innovation in rapid information processing.

Information Strategy

The information strategy defines how the enterprise can benefit from big data and why it's important? We have to uncover the business opportunities we can derive from big data. We need to make the strategic decisions that will transform enterprise business.

Big Data Information Strategy

  • Strategy: Is the organization prepared for an information-led transformation? How will we harness big data to improve enterprise strategic decision making? We need to know which investments will deliver the most business value and ROI.
  • Governance: How will you govern your organization's information assets in support of your enterprise information management (EIM) goal? Are there new expectations for information quality and management?
  • Talent: By 2015, Gartner predicts that 4.4 million jobs will be created around big data. Does your organization lack the "data scientist" talent required to exploit big data? How will you assemble the right teams and align skills? 

Data Analytics

Big Data Analytics

T is under pressure to tap into growing quantities of data to help the business make better, informed decisions by combining new sources of big data with existing enterprise dark data. How will you uncover more customers and business insight and more data value? 

  • Predictive Analytics: How are you using data for predictive and real-time analysis across various business domains? How can you use unstructured enterprise information and data to drive a better client experience? How are you leveraging new data types: sentiment data, clickstream data, video, images and text data?
  • Behavioral Analytics: How will you tap into complex data sets to create new models to drive business outcomes, decrease costs, drive innovation or improve customer satisfaction?
  • Data Interpretation: What new business analysis can be drawn from your data? How will IT help support insight discovery and new information trends? You need to know which data to integrate for new product innovation.

Enterprise Information Management

Enterprise Information Management

What are you doing with all of the data your organization collects? You have many data disparate sources – from your enterprise's "dark data" and partner, employee, customer and supplier data to public, commercial and social media data – that you need to link and exploit to its fullest value.

  • User expectations: Your employees are demanding more access to big data sources. What's your plan to manage access to these information sources? What are the use cases?
  • Costs: How can you deliver access to big data in a rapid and cost-effective way to support better decision-making? 
  • Tools: How will you link these new sources of diverse data? You need to plan the impact on your data center. Have you identified the processes, tools and technologies you need to support big data in your enterprise?

 

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