The 7 Questions Interview Series: Data and Supply Chain Data Integration
The 7 Questions Interview Series: Data and Supply Chain Data Integration “The 7 Question Series” is an investigative content series where we seek out key leaders in a specific industry and/or subject matter expertise area and ask them 7 key questions that “enquiring minds want to know”. There is a twist however to these questions. We provide the person being interviewed with a hypothesis for each question. This helps to frame and set context for their answer.
Data and Supply Chain Data Integration Series Objectives:
Data and Supply Chain Data Integration Series Objectives: The objective of this series is to establish direct connections with data experts across the globe and ask them the same set of 7 questions regarding data and data integration in the business. We want to derive insights from their direct experiences and expertise that will help companies, both B2B and B2C at all stages of their evolution. We are also curious to see if their answers are similar or different. These interviews will be featured on this website as a series.
Interview with Val Matison, Independent Management Consultant:
Val Matison is an independent consultant providing information management consulting services for business intelligence and data governance initiatives and providing overall information strategy. His information consulting experience includes verticals such as finance, health care, consumer packaged goods, retail and the public sector. Val advise clients on the evolution of their information strategies and has led a number of governance and operations transformations. Technically, Val possess a strong understanding of databases, architecture and data analytics but his focus is on delivering value to the business. Previously he was a Senior Strategist at PwC where he identified opportunities across lines of service in business intelligence and other practices.
Robin Smith: Has the term Big Data been over hyped? There a sense of “Big Data” fatigue, backlash even, that seems to be becoming more prevalent. Is Big Data relevant?
Val: I think the term Big Data is relevant in that there is a pervasive amount of data in every aspect of our lives. This comes from business and personal perspectives. Getting data is cheap and easy. In my experience businesses over think data and forget the low-hanging fruit when it comes to analytics.
Robin Smith: Do you really need data scientists as part of your big data strategy? What are the characteristics required of a data scientist? Does this have implications for our educational systems?
Val: A data scientist should be a renaissance person. Someone who can work with many aspects of technology and business with skills in algorithms, statistics, business process, data mining, domain knowledge, process mining and databases to name a few. I feel a data scientist is seasoned individual who has a background in some or many of these areas. It’s part art and part science.
Robin Smith: Is the relational database, the foundation of the data warehouse in the small data world, still relevant in a big data age?
Val: Relational data has not gone away and is alive and well and will continue to be part of the data landscape for many years to come. Many big data implementation give up a lot in the way of veracity of the underlying data stored within those data sets. This does not suggest the data isn’t valuable but it does not meet the stringent requirements of typical transaction-based systems.
Robin Smith: Given the reputation and organizational risks involved in poorly governed data (privacy, breach, quality), should data governance be a corporate governance imperative? Where should ownership of this risk reside, should a company have Chief Data Officers?
Val: Data is the new oil and not treating like an asset is asking for trouble. Senior leadership within an organization needs to understand what data is, it’s value and why it’s a strategic asset.
Robin Smith: Is big data only for big companies with deep pockets?
Val: This really depends on the value that can be obtained from a big data implementation. A small firm that has lots of internet transactions could leverage a big data implementation. But I don’t see a small shoe store chain benefiting from such an exercise as traditional relational systems will typically meet their needs.
Robin Smith: How has Data changed the way business should look at their systems?
Val: Data and how it’s leveraged is how businesses can differentiate themselves from one another. For example if a business understands the needs of a customer and how that customer interacts with the business, they will ultimately benefit from that knowledge. This applies to the entire buying cycle: activation; search & evaluation, intention, decision, and consumption.
Robin Smith: Data ownership and value has become the latest discussion point in the data hype cycle. Has the accounting and legal paradigm changed enough for data to be defined as an asset on the balance sheet and has ownership been clearly delineated from a legal perspective?
Val: It’s hard to quantify what has different values to different people. In the hands of an intelligent data scientist, data becomes very valuable since they know how to use it. On the other hand terabytes upon terabytes of data residing on hard drives is useless. It’s the context and leveraging of data that gives it value.
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