63 )List and describe four of the most critical success factors for Big Data analytics Answer: a clear business need (alignment with the vision and the strategy ) Business investments ought to be made for the good of the business, not for the sake of mere technology advancements Therefore, the main driver for Big data analytics should be the needs of the business at any level-strategic, tactical, and operations Strong, committed sponsorship(executive champion). It is a well-known fact that if you dont have strong, committed executive sponsorship, it is difficultif not impossible)to succeed If the scope is a single or a few analytical applications, the sponsorship can be at the departmental level. However, if the target is enterprise-wide organizational transformation which is often the case for Big Data initiatives, sponsorship needs to be at the highest levels and organization-wide Alignment between the business and It strategy. It is essential to make sure that the analytics work is always supporting the business strategy, and not other way around. Analytics should play the enabling role in successful execution of the business strategy A fact-based decision making culture. In a fact-based decision-making culture, the numbers rather than intuition, gut feeling, or supposition drive decision making. There is also a culture of experimentation to see what works and doesn't To create a fact-based decision-making culture senior management needs to do the following: recognize that some people can't or won't adjust; be a vocal supporter; stress that outdated methods must be discontinued; ask to see what analytics went into decisions; link incentives and compensation to desired behaviors A strong data infrastructure. Data warehouses have provided the data infrastructure fo analytics. This infrastructure is changing and being enhanced in the Big Data era with new technologies. Success requires marrying the old with the new for a holistic infrastructure that works synergistically Diff: 2 Page Ref: 379-380 Copyright C 2018 Pearson Education, Inc10 Copyright © 2018 Pearson Education, Inc. 63) List and describe four of the most critical success factors for Big Data analytics. Answer: • A clear business need (alignment with the vision and the strategy). Business investments ought to be made for the good of the business, not for the sake of mere technology advancements. Therefore, the main driver for Big Data analytics should be the needs of the business at any level—strategic, tactical, and operations. • Strong, committed sponsorship (executive champion). It is a well-known fact that if you don't have strong, committed executive sponsorship, it is difficult (if not impossible) to succeed. If the scope is a single or a few analytical applications, the sponsorship can be at the departmental level. However, if the target is enterprise-wide organizational transformation, which is often the case for Big Data initiatives, sponsorship needs to be at the highest levels and organization-wide. • Alignment between the business and IT strategy. It is essential to make sure that the analytics work is always supporting the business strategy, and not other way around. Analytics should play the enabling role in successful execution of the business strategy. • A fact-based decision making culture. In a fact-based decision-making culture, the numbers rather than intuition, gut feeling, or supposition drive decision making. There is also a culture of experimentation to see what works and doesn't. To create a fact-based decision-making culture, senior management needs to do the following: recognize that some people can't or won't adjust; be a vocal supporter; stress that outdated methods must be discontinued; ask to see what analytics went into decisions; link incentives and compensation to desired behaviors. • A strong data infrastructure. Data warehouses have provided the data infrastructure for analytics. This infrastructure is changing and being enhanced in the Big Data era with new technologies. Success requires marrying the old with the new for a holistic infrastructure that works synergistically. Diff: 2 Page Ref: 379-380