By Masha Tseveen.
This week, we’ll be featuring Rachel Bland. If you missed our previous posts, be sure to check out our interview with James Kobielus and Nancy Kopp-Hensley. Please join the conversation by commenting below!
Rachel Bland is a senior product manager from the IBM Business Analytics team. Rachel has 15 years of experience in implementation and product management of data modeling, warehousing and query processing for Business Intelligence. Furthermore, Rachel has been involved for several years working with IBM Business Partners developing patterns of expertise for the IBM PureApplication System. Rachel has shared her experiences as a frequent speaker at IBM Information on Demand and IBM Impact conferences and is the author of a number of whitepapers on the topic of modeling and query best practices with IBM Cognos Business Intelligence.
How would you explain Business Analytics to a people who are not familiar with it?
Think about bank statements and budgeting, or any activity you do where you need data to help inform your decisions. Some of the data you need is activity generated like credit card and ATM records, some of it comes from the bank like your interest rate and payment due dates, and some of that information is manually entered or collected, like what you expect to pay for a new car. You may use that information to create a budget for your household, looking up other information about the average % of income people spend on housing and transportation from a government website and compare your spending to that amount. You’ll probably consider adjusting your spending as you build a plan to buy a home, upgrade your car, or forecast what it will cost you to get married and start a family. Whatever your purpose you will collect data, make a plan or a projection and then you keep checking and comparing, adjusting as necessary to achieve a goal. That’s how business analytics works in a company: You gather data based on your operations, your industry, etc… and put it together so that you can understand what is happening, compare it to what you want to happen, use other sources of information to determine what you think will happen next and monitor frequently, adjusting as necessary. It’s just on a much larger scale that can focus on a particular product, brand, region, or span divisions in a multi-national company.
What is the biggest challenge of analyzing big data today? What IBM is doing to address the challenge?
Volume, velocity, variety and veracity. It’s overwhelming, There’s a ton of data out there, sometimes it’s hard to know where to begin, what part of your business is most ready, which part is most in need, how do you harness and transform your data into information? Some of that data is just too big and moving too fast to work with in a traditional sense. Think about topics trending on Facebook or Twitter, if your name or company is trending you need to know that immediately, not tomorrow or next week, as there is a temporal nature to the usefulness of the data that contrasts with the size of the data. You need small slices at the right time. Then there is the whole issue of truth. What data is useful, what data is correct, is it from a trusted source and does it jive with your data? You may think you understand customer Jon I Smith until you call him at a series of wrong phone numbers and find out “he” is actually a woman (Joni) who stopped doing business with your company 2 months ago. Finding out why could be the next step and much more interesting than the original analysis you began!
IBM has solutions, skills and tools to help, wherever you are in the analytics journey, whatever your priorities; we build hardware, middleware and application software, we cultivate numerous developer communities and support open source initiatives. In the realm of business analytics alone, you can do so many things with IBM. For example, you can start with understanding your customers with a customer analytics application on your desktop based on an offering like IBM Cognos Express, or implement IBM Cognos Enterprise BI with IBM SPSS for an interconnected customer satisfaction application that leverages predictive algorithms to assist customer service representatives with making better suggestions and recommendations during precious interaction time with your clients. You can leverage IBM Big Insights and IBM InfoSphere Streams with PureData Systems to capture all manner of data and build a data foundation that brings together all your information assets in a way that poises you to use analytics to find opportunities or operate more efficiently to differentiate yourself against your competitors and within your industry. IBM has a combination of industry and technical expertise in areas as diverse as Aerospace & Defense to Media and Entertainment, and a network of partners that is unparalleled in the industry.
You have 15 years of experience in data modeling, warehousing and query processing for Business Intelligence. What is your personal favorite IBM Business Intelligence tool or software program of all time? Why?
Well… IBM products are numerous and many of them are fairly large in scope, but I think the Workspace Advanced functionality of the IBM Cognos BI suite combined with Dynamic Cubes is probably my favorite. I began my career doing ETL and data warehouse design for Cognos Transformer and PowerPlay, those tools opened my eyes to the power of what can be discovered by humans interacting with data. With Workspace Advanced and Dynamic cubes the user interaction experience is combined with brilliant performance over huge amounts of data; that really comes to life in the hands of a business analyst. Queries that we used to expect to take hours now come back in seconds which makes it possible to think your way through a data set, truly exploring and learning about what’s happening in the business with significantly larger data volumes than ever before. Combined with predictive analytics this functionality is going to lead the way for organizations who want to be looking forward rather than backward.
If you were hiring a person for business analytics job, what skills and traits would you look for?
Key skills are problem solving and an understanding of how data is captured and transformed. From an education perspective, I always look for people who enjoyed math in school, relational algebra, linear algebra, etc… as I’ve found these people tend to have an aptitude for understanding what it takes to discover data, profile data and transform it into a wide variety of useful insights. To be fair that’s how I got here, I was majoring in Applied Mathematics until I took my Computer Science elective and decided I had to do both majors. My background in mathematics has been every bit as useful as my computer science educations. From an experience perspective I look for people with experience in customer service or application implementation roles, who understand what it is to take the tools and resources you’ve got and add value in service of the client.
In your opinion, what characteristics succeed and thrive in this organization?
Skills and creativity are obviously important, but so is an ability to understand the strengths of your team. None of us are able to solve all of the problems we discover alone and being able to build strong relationships within your team as well as outside your team so you can call on educated opinions and the experiences of others is what allows you to take things to the next level. When you work in a company of 400,000 people it can be intimidating, but my experience at IBM is that people are very willing to be generous with their time and knowledge and if you follow the Six degrees of separation concept you can find an expert in just about anything to point you in the right direction to learn about new technology, new problem spaces or industries.
What are the most memorable moments of your career, things that make you smile whenever you think about them?
Well…there are a lot of those. I’ve been part of several 1.0 product releases during my career and my general experience is that during each project you reach a point of momentum and things falling into place where you just can’t help feeling a buzz. Also, with 1.0 products, after all the hard work and long days and nights there comes a point where you feel it take hold in the market and that feels amazing!
What three pieces of advice would you give to people who would like to follow a career path similar to yours?
Don’t limit yourself in your career path too early on, keep your doors open. If you have the opportunity to diversity in your education, do so. Take some business courses, take some courses in other subject matters, chemistry, geology, anthropology… IT is not really just about computers, it’s about applying technology to solve problems in many diverse industries.
Get experience in different industries, don’t assume programming in a software company is the only valid experience, work in a not for profit, a university lab or an IT shop for a company in an industry that interests you and keep your eyes open. Understand what works well and why, understand the value technology brings to the business.
Mix and mingle… Very often the intensive nature of computer science or business programs lead to students staying within a smaller social circle. Try to find a way to cross-pollinate, you’ll always need to mix with people who have different perspectives and priorities in life and the work world. Get comfortable with it early, join an activity at school that takes you out of your social comfort zone, especially things that get you comfortable with public speaking and presenting your thoughts and opinions.
Anything else you would like to share?
Life takes you places you never expect. I started university in life sciences and finished in math and computing science. I started my career in programming and ended up in product management. I discovered my aptitudes through taking different assignments and trying out different things and ended up becoming an expert in data warehouses and metadata, I’ve worked with partners and clients, been a product manager working in multiple areas including the appliances space, and now I can use all those experiences in my current role seeking growth opportunities for IBM Business Analytics. Looking back, it’s been a pretty good deal, it’s provided a great life with lots of great experiences and friends along the way. I wouldn’t change a thing.