This week I interviewed Director of Business Intelligence and Analytics at Arbela Technologies, Brandon George to educate us about the prerequisites necessary to get to the data analytics truth inside an organization.
Q: Brandon, I had the good luck to hear you present the prerequisites for Business Intelligence inside an organization. What can you tell me about prerequisites for Business Intelligence why is that important?
A: Talking prerequisites is talking about what you should focus on first to make sure you are successful. A lot of people get lost in the technology - they focus too much on the technology and may not have a solid starting point. A lot of people want to jump straight into predictive analytics when in reality they need to establish trust with their people, data, and processes at the descriptive step. The what, where and why’s of BI. This is the reason having a right focus on prerequisites is a must.
Q: What is BI and what is the approach?
A: It’s people and data and connecting those two elements at the intersection of the workflows that make up their daily lives. It is enabling decision that is timely and based on fact. Further, it is establishing the ability to go beyond the traditional reporting mindset and into a new truth where data becomes a perspective partner in helping customers achieve their desired business outcomes and beyond.
Q: What’s a good example of people and data connecting?
A: Say you have a sales rep in the field and he has the data he needs in the palm of his hand so he can correctly gauge with the customer he is going to talk to – it’s contextually relevant – it’s in the natural element – they are able to consume it in their natural workflow which is mobile.
Q: When someone says, they don’t need BI because they can develop all the ‘reports’ they need, what do I take from that?
A: It’s a common mindset that is reactive in the sense of how people are used to engaging with their data. This way of thinking is something we face all the time. We address this by helping customers realize that their data can become a valuable and proactive data asset. Seeing this in action helps customers understand the change from reactive searching to proactively engaging with their data, in a timely and relevant manner.
This is done in a collaborative and iterative fashion that is easier to consume because of our agile approach. We are helping they go from reporting mindset to a data-driven culture. We do that by giving great examples they can relate to, and it follows their workflow and answers the questions they care about.
Q: How do you explain that to new BI customers?
A: An example is when a customer has an Excel report that shows their sales breakdown versus forecast. Someone must dig through a pivot table to find areas of concern that needs focus. This takes time away from such resources being able to focus on more higher value data analysis. A proactive example is instead of having someone waste time, we make it and set it up so that their answers come to them and what they see are the problem areas they should focus on. Removing the need to dig through data. This is what we can action-oriented insights.
Q: What are initial prerequisites to going from reactive to proactive to get the truth? What we call here at Arbela our maturity model.
A: Prerequisites across the maturity matrix categories include and can be seen in more detail at www.arbelatech.com. These questions summarized below begin defining the truth:
- ORGANIZATION: How widespread are analytics across your organization and are roadmaps in place?
- INFRASTRUCTURE: How advanced and widespread is the architecture to support analytics and what key resources are in place?
- DATA MANAGEMENT: What types of structured and unstructured data are required, what is the frequency, and integration in place?
- ANALYTICS: What is the scope of the analytics and how widespread including consistency, method of delivery and integration?
- GOVERNANCE: How clear is the organization's data governance, how restrictive are the self-discovery and are there security policies for data access?
Q: So now that a customer has answered the pre prerequisites, do they buy a product?
A: I don’t believe you can buy business intelligence. This is always a core belief of mine. I don’t believe BI is technology either. Unfortunately, that seems to be the focus for a lot of people. Because of this technology deluge, some of the greatest intentions fail. You come back to the focus of what outcomes do you want. Then having an iterative and collaborative approach to delivery that is focused on the desired questions to be answered daily, weekly and monthly for specific personas. You don’t select a hammer and think now I can build a house. You must understand what you are trying to achieve, so then you can select the correct toolset to achieve the desired outcomes.
Q: So, customers are facing silos. They’re facing spreadsheets, archived data, and real-time data. Is the accomplishment bringing all of that together and making it intelligent?
A: Yes, and that is just the starting point but the real value with our jumpstart and bringing that together is the next level. Where your data can start to prescribe things to you. It can become an asset – like inventory – reduce your inventory by millions of dollars a year.
Q: We are proud to have data scientists on our Arbela team. What is the difference between a data analyst, a data architect, and a data scientist?
A: Typically, a data scientist usually focuses on the prescriptive and predictive end of analytics. If you look at this as a spectrum, then the data scientist role is working with stats, models and algorithms – focused on delivery of almost hyper-scale proactive insights. A data analyst role is typically a person that focuses on the presentation layer and working their way inwards towards the semantic and data itself. Whereas the data architect is typically a person that is focused on that all-important business semantic layer that becomes the glue in which ties all this business intelligence spectrum together across the enterprise. There are a lot of other items I could spend an entire interview on for each role, but hopefully, this helps paint the right picture.
Q: From here, how do users get to the truth about their data?
A: At Arbela, we know the questions. If users have the answers we can help them find the truth! We can do this for users as full-scale projects with roadmaps for companies who have budgeted business intelligence. For companies that just want to get started in a small area, they can engage us as needed through our Arbela OnDeck program. We offer one free hour of consulting services. Visit the page below and fill out the form to submit new requests via http://www.arbelatech.com/services/arbela-ondeck.html.