Big Data: Understanding How Data Powers Big Business

Successful advanced analytics capability for marketing organizations involve integrating point of sale (POS), demographic, behavioral, social, mobile, CRM, third party web and retail loyalty program, digital marketing platform (DMP), psychographic and channel attribution data into insights for activation on demand-side platform (DSP), social media, segmentation, pricing, new product development and media mix optimization. At my organization, we’re starting our big data journey with a focus on digital marketing and will roll in additional programs - including pricing, segmentation, new product development, marketing mix optimization and integrated supply chain - as we develop this capability. I’ve been researching big data through consultants and in-house experts, and I’ve found Bill’s book to be an enormous help. His insights into the process before the implementation are things that other big data firms won’t share (or simply don’t know). He’s leveraged his many years of big data expertise with Yahoo!, P&G and now EMC to create this powerful tool that will help any firm determine the necessary steps to take on their big data journey. The 3 steps for implementing a big data analytics infrastructure include: 1. Understand personas (decisions, questions, KPIs) 2. Identify a process for data ramifications (how does data impact my value drivers) 3. Assess user experience (format of analytic results for decision-makers) If you read one book on big data, this should be it. Bill Schmarzo is an expert in big data and his book is sure to provide the information you need to understand the complex world of advanced analytics and guide you through the process of developing your own big data capability.

I especially appreciated the cross functional aspects described in the book and the practical workshop moderation recommendations. A very useful guide to big data and its role in a modern company.

Item was delivered on time and as described.

Good

Great resource

Bill's book is an excellent, practical approach to big data. The first half of the book is about big data and how it can help businesses make more money. The second half of the book is Bill's methodology, step-by-step approach, to begin a corporate strategy around big data. This book is very informative and relevant to business and how to incorporate another tool, big data, into the business strategy matrix. Book Summary/Overview: Big data is more about business transformation than just the next technology ‘silver bullet’. It is about making money. Big Data – Analyzing and assessing all data sets rather than using a subset of the data to represent the whole. Key Model Concept: • Below is Bill's framework for Big Data maturity: Where is your company on the continuum? 1. Monitoring a. Using: Dashboards, Success Factors and KPIs Why or move? The three Vs: Volume, variety and velocity make data management very difficult. 2. Insights – Four business drivers are needed: a. All corporate data should be included b. All unstructured data including: i. External data: Social media, mobile, etc. ii. Internal data: Consumer comments, email logs, etc. c. Real-time data access d. Predictive analytics directly related back to your business processes i. Example: Which customer group responded best to an ad, event or request? That immediate feedback is critical. Why move? A user needs these four insight drivers to begin making business recommendations. The business recommendations lead to…. 3. Optimization a. Analytics can now be best integrated and key business actions can be automate: i. Example: Customer pricing discounts can be immediately modified based on all prior behavior. Instantaneous feedback and automatic action. ii. Machine learning 4. Monetization – Three ways business Insights are turned into money a. Resell insights to other business partners and parties b. Integrate insights into physical products (cell phones, cars, etc.) c. Align insights on a customer by customer basic for a better user experience. 5. Metamorphosis - Allowing other companies and customers to make money off of big data insights. a. This must be done carefully to avoid the ‘creepy’ factor from customers. Big Data History: 1970s, 1980s and key events are discussed. Business Impact of Big Data (If you like baseball – read this section) • Use the right metrics to gain a business advantage • Continually reinvent iterations to keep relevant and a competitive advantage • This section in the book also describes how to monetize your data Impact of Big Data on your business • Business Intelligence Analyst (BI) vs Data Scientist o BI: Usually works in a data warehouse generating reports and dashboards o Data Scientist: Usually works in a ‘sandbox’ modelling, testing and refining • New roles in organizations to address these new challenges Decision Theory • Analytics applied to massive data leads to: o Great insights based on data rather than on one’s gut o Focus on future trending, future expectation and predictable actions based on all data sets and logic. There is less likelihood to get caught up in one’s feelings and guessing at cause-and-effect relationships. The 2nd half of the book describes how to implement Big Data solutions. Big Data Strategy • The ‘how’ to put together a big data strategy (quite straightforward): o Biz Initiatives o Desired outcomes o Tasks The Value Creation Process • Define your most: o Valuable customers o Important products o Successful campaigns • Value Chain Analysis o A methodology is outlined how each business unit adds value to the products the company produces. Big Data User Experience Ramifications Identifying Big Data Use Cases Solution Engineering • There is no silver bullet with Big Data. Understanding your business is key to a successful Big Data project and implementation. Big Data Architectural Ramifications Launching Your Big Data Journey Next Steps

If you were stranded on a desert island and needed to develop a big data plan for your organization before you were allowed to get off, I would start with this book. Just published in Oct 2013, EMC's Schmarzo delivers the practical goods on how to stand up big data in your organization. Schmarzo not only provides a good overview of BD as well as the products and the big data tools and their functions but also, the path and a number of business cases on how companies benefit from adopting this technology. On your big data journey, start here. You won't regret it.

The book did an outstanding job of pulling together topics like Decision Theory, how to create Big Data strategy, Big Data architectural ramifications and of course an excellent chapter on the Value Creation process and models by Michael Porter. Bill Schmarzo is often called the "Dean of Big Data" and he doesn't disappoint. Quick read and worth adding to your technical library.

Good Book to understand what big data is. Tis book doesn't explain any big data projects. Bu, it will give an overall idea