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Big Data and the different types of decision

For McKinsey Global Institute, Big Data is the next frontier for innovation, competition, and productivity. IT experts say that Big Data challenges are more than data size and require new technologies like Map Reduce. Big Data conduct to new analysis requiring more than SQL, and need specific analytic platform in order to manage relational plus non-relational data sources. At the end Big Data analysis bring new insights that could facilitate business decisions.

Management gurus agree to distinguish four levels of decision making for businesses. Strategic decisions define the relationships between the company and its environment (choice of activities, markets, technology clusters, ...), they set axes and policies for the long term. Organic decisions define the organizational structures, processes, information systems (business, mission, delegation, responsibility, resources, ...), they set the framework for the medium term. Management decisions for the short term set the direction and expected performance (objectives, resources, control, ...). Finally, operational decisions are interested in the daily operation, in supervision of the execution. As Big Data analysis is emerging it is actually difficult to find a lot of business uses cases, for each type of decision above, showing the value added by this new approach.

Did Big Data analysis will transform decision process? Probably not but it could enrich it. Faced with a decision a manager can adopt different behaviors such as not to decide, leave it to chance, act then think, trust his intuition, think solo, analyze the numbers, turn to a third party, opt for the collective and finally do as everyone else. Whether working alone or not, using some resources or not, if he does not refrain, it goes through four phases of decision-making. A training phase with gathering information to identify the problem, opportunities and define what can make a difference (here Big Data could help). A design phase to identify and model options, identify and evaluate solutions. A selection actions phase comparing choice and predictability of earnings. An implementation phase and finally an evaluation phase of results.

So if Big Data could bring new insights, what is sure actually, is that you cannot use universal solution, and you should establish a mix of resources to manage all types of data needed. That’s why Teradata multiplied partnerships to offer its customers the best application solutions in the market, and bought earlier this year the company Aster Data, which provide the opportunity to take better account of unstructured data or multi-structured data.

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