By David Loshin (Auth.)
Big facts Analytics will help managers in offering an summary of the drivers for introducing gigantic information expertise into the association and for knowing the categories of industrial difficulties most fitted to special info analytics suggestions, knowing the worth drivers and merits, strategic making plans, constructing a pilot, and at last making plans to combine again into creation in the enterprise.
- Guides the reader in assessing the possibilities and cost proposition
- Overview of massive facts and software program architectures
- Presents a number of applied sciences and the way they healthy into the large info ecosystem
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Extra info for Big Data Analytics. From Strategic Planning to Enterprise Integration with Tools, Techniques, No: SQL, and Graph
Move into production: If the technology appears to add value, strengthen the plan to move it into production. 6 ROLES OF ORGANIZATIONAL ALIGNMENT Executing this sequence in alignment with organizational needs requires people who can champion new technologies while also retaining a critical eye to differentiate between hype and reality. Aside from the boots-on-the ground folks like big data developers and data scientists, below are some roles of organizational alignment played during the consideration, evaluation, and decisioning process for assessing the value proposition for big data: • Business evangelist: This individual understands the types of performance barriers imposed by the existing technical infrastructure and Achieving Organizational Alignment for Big Data Analytics • • • • • 27 understands that ongoing reviews of emerging technology may create efficiencies that do not currently exist within the organization.
Engaging the consumers for requirements is a process of discussions with the known end users, coupled with some degree of speculation and anticipation of who the pool of potential end users are, what they might want to do with a dataset, and correspondingly, what their levels of expectation are. Then, it is important to establish how those expectations can be measured and monitored, as well as the realistic remedial actions that can be taken. 2 Identifying the Critical Dimensions of Data Quality An important step is to determine the dimensions of data quality that are relevant to the business and then distinguish those that are only measurable from those that are both measurable and controllable.
In any technology adoption cycle, it is incumbent upon the key stakeholders in the organization to make sure that the business process owners, the information consumers, the technical infrastructure innovators, the application developers, and the enterprise architects all work together in an environment that can continue to satisfy existing reporting needs yet is flexible enough for exploratory work. 1) to help us consider how to manage the transition into a production development process to take advantage of the business value big data techniques can provide.
Big Data Analytics. From Strategic Planning to Enterprise Integration with Tools, Techniques, No: SQL, and Graph by David Loshin (Auth.)