Simply your analytics strategy

Simply your analytics strategy

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  Simplify Your Analytics Strategy Submitted by:Saurabh Ranjan Institute: Jadavpur University Under the guidance of : Prof.Sameer Mathur
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  Steps to simplifythe analytics strategy and generate insight that leads to real outcomes: 1. Accelerate the data: 2. Next-Gen Business Intelligence (BI) and data visualization. 3. Data discovery 4. Analytics applications. 5. Machine learning and cognitive computing.
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  1. Accelerate thedata Fast Data Fast Insight Fast Outcome
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   Liberate andaccelerate data by creating a data supply chain built on a hybrid technology environment — a data service platform combined with emerging big data technologies. Such an environment enables businesses to move, manage, and mobilize the ever-increasing amount of data across the organization for consumption faster than previously possible. Real-time delivery of analytics speeds up the execution velocity and improves the service quality of an organization.
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  2. Next-Gen Business Intelligence(BI) and data visualization.  Next-gen business intelligence is bringing data and analytics to life to help companies improve and optimize their decision-making and organizational performance. BI does this by turning an organization’s data into an asset by having the right data, at the right time and place (mobile, laptop, etc), and displayed in the right visual form (heat map, charts, etc)
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  3. Data discovery Through the use of data discovery techniques, companies can test and play with their data to uncover data patterns that aren’t clearly evident. When more insights and patterns are discovered, more opportunities to drive value for the business can be found.
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  4. Analytics applications Applications can simplify advanced analytics as they put the power of analytics easily and elegantly into the hands of the business user to make data-driven business decisions. They can also be industry-specific, flexible, and tailored to meet the needs of the individual users across organizations
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  5. Machine learningand cognitive computing  Machine learning is an evolution of analytics that removes much of the human element from the data modelling process to produce predictions of customer behaviour and enterprise performance.  Software intelligence is helping machines make even better-informed decisions.
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  Managerial relevance  Amanager should understand that there are many different elements in play when it comes to simplifying analytics and they are always changing, for example business goals, technologies, data types, data sources, and then some are in a state of flux. A manager should be willing to change the conservative culture of company if need be and should be willing to take chances.  He should know whether the company have a plethora of existing data and analytics technologies to work with, or is it just starting out with its first analytics project.  Then the manager should take the above mentioned steps to simplify the analytics.