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Big data is useless without visual analytics

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With its vast volumes, big data is useless without the analytic and presentation functionality of visual analytical tools.

Think how difficult it is to spot anomalies or trends in endless rows of spreadsheet data. Visual analytic tools solve that overload problem.

Big data is an in-vogue topic in the information technology world. Many executives see that it opens up transformative possibilities for products, services and markets.

This understanding has sparked massive investments in software for visual analytics and business intelligence, and related cloud-based services. The sales of this software will grow significantly in the future. Wikibon, a community of business technology practitioners, projects the big data market will top US$84 billion in 2026, attaining a 17 per cent compound annual growth rate for the forecast period 2011 to 2026.

Big data refers to the vast data volumes being produced by:

Because of its large volume, big data is difficult to analyze meaningfully for business value. Let’s assess the tools many organizations routinely use to analyze their data and see how successful each approach really is.

Visual analytics is just right for big data

Visual analytics is a component of business intelligence software that emphasizes:

Visualizations are valuable because they display a lot of data in an easy-to-understand format that works well for our visually-oriented minds.

Business intelligence software is a set of tools for acquiring and transforming raw data into meaningful and valuable information for business analysis and improvement.

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Overall, business intelligence software packages are growing suites of software that:

However, business intelligence is undermined by a lack of:

Data mining is too complicated for most uses of big data

Data mining is the automatic or semi-automatic analysis of big data to extract previously unknown patterns that may be useful for business improvement. Data mining techniques include artificial intelligence and machine learning.

Overall, data mining:

However, data mining:

Classical reporting is too ponderous for big data

Some organizations have made significant investments in software tools and development to produce a rich library of reusable data analysis reports where the end-user can dynamically vary the data selection criteria. Leading examples are SAP Crystal Reports and Oracle Reports.

Overall, reusable reports:

However, reusable reports:

Excel is too restrictive for big data

We’ve all heard that Excel is the leading tool for data analytics. It’s widely and successfully used by organizations of all sizes for primitive applications, simple tools and modest data volumes. Excel is also widely used as a powerful personal productivity tool within many larger organizations where information systems department responsiveness is a problem.

Overall, Excel is:

However, Excel:

Ultimately, then, visual analytics is dramatically superior to the alternatives for achieving business value from big data.

Yogi Schulz has over 40 years of information technology experience in various industries. Yogi works extensively in the petroleum industry. He manages projects that arise from changes in business requirements, the need to leverage technology opportunities, and mergers. His specialties include IT strategy, web strategy and project management.

Yogi is a Troy Media contributor. For interview requests, click here.

The opinions expressed by our columnists and contributors are theirs alone and do not inherently or expressly reflect the views of our publication.

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