iVEDiX BI Buzzword Breakdown | Business Intelligence Definitions
Based on Software Advice‘s BI Buzzword Breakdown: 5 Experts Tackle 3 Business Intelligence Definitions
CIO, BI, IT, OLAP, ETL, BYOD and let’s face it … IDK. When it comes to mobile business intelligence (BI) the industry is swamped with jargon and buzzwords. And if you’re at your wits end, maybe iVEDiX can help. We’re a diverse sect of BI industry professionals, whose mobile app, miVEDiX, simplifies the complexity of not only BI terms, but also industry trends, data quirks, and preferences.
Nevertheless, education is a big part of BI, so our CEO, CIO, Services Architects and Marketing Director are going to share just what these terms mean to them:
What is Big Data?
Big Data, until the advent of unstructured content used to be confined to volumes of structured content. This was relatively finite in that scale and capacity was predictable and ‘plan-able’. This varied from one industry to another of course but in general, retail and telecom sectors saw the most volume. The inclusion of unstructured content into the analytic mix has created a new paradigm for ‘Big Data’ zealots. The management of this new eco-system is simply a case of going back to the fundamentals. Data modeling, meta data definitions, open standards and lowest common denominators of mapping and some intense business process redefinition.
Does not mean anything, size is purely arbitrary. Just a “buzzword”, non-technical people like to use, thinking it is: “au gout du jour”. To me, assuming it represents something, it would be the entire data on the web, essentially behind the social media sites. But does that deserve a new term?
Big Data at it’s most basic is a data set so large that it becomes burdensome for companies to use or maintain. Big data is interesting because this massive volume of data contains so much information that new and interesting insights could be gained through proper analysis and utilization of these massive data sets.
Big Data is all the information outside your organization. Years of Facebook comments and Pandora ‘likes’ yield a degree of more information about someone than any internal data system. Big Data is about being able to analyze this daunting amount of information and discern something relevant. Marrying these trends with your internal data system helps to answer questions such as “what is thereal demographics that we should be selling to.”
Skyscrapers overflowing with paperwork, or so I thought. I’ve realized big data is more than output – that’s only what it is when it’s unorganized and under managed. Big data can empower your people, your customers, and your future if it has the analytic power to back it up.
What is a Data Warehouse?
The Data Warehouse of the future will serve as a pit stop for content defined, tagged and staged for performance. It will play a supporting role to the ubiquitous data model. Traditional Vendors will be forced to support cross-platform standards of retrieval and storage.
I would stay with the very concise and accurate definition from Wikipedia: “A data warehouse (DW or DWH) is a database used for reporting and analysis”. Nothing else to add unless you are willing to digest hundreds of pages; if so, I recommend both Kimball’s and Inmon’s books, respectively “The Data Warehouse toolkit” and “building the Data Warehouse”; be careful of indigestion though!
The data warehouse is a large store of data that serves as a central integration point for a companies source systems, such as a financial and inventory data. This data warehouse can then be used for analytics and reporting to provide an organization with information on how to make more informed business decisions which can ultimately save time and money.
The ultimate repository for every piece of information in your company- from payroll records for the past 10 years to the current retail prices for products. Data warehouses are the backbone to any information system and as with any infrastructure- they need to be carefully planned, maintain and monitored for data quality. The last thing a company wants is for payroll records to become corrupt…
A lot like a teacher whose students pass their papers to the front of a class room, everyone puts in something different, but when they’re collected the teacher becomes the main source for names, averages, grades, ect. When the influence of a data warehouse is realized, it can generate insightful feedback to build, benchmark, and forecast success.
What is Data Mining?
Data mining is evolving into less mining and more fracking. I’m not necessarily endorsing the practice but using the science as an analogy to make the point that content retrieval is going to be focused, scientific and driven by meta- data definitions. This will be true of structured or unstructured content ‘mining’ and pattern recognition.
Another kind of buzzword without too much interest. In my mind, that is a just a term for describing a would-be more sophisticated data analysis, essentially to find patterns in data. But what would be a comprehensible boundary between basic and sophisticated data analysis? To prove the vagueness of this concept, to my knowledge, nobody has been capable to place “Data Mining” in a well-established computer science discipline.
Data mining is an automated process in which data is analyzed to discover patterns, trends, relationships or other insights within data sets. Discovery is the key here when talking about data mining since the primary focus of data mining is to find the insights that we normally wouldn’t see or even consider. Organizations can then take advantage of this information to cut costs or increase profits.
Data Mining requires Data Scientists- highly perceptive individuals who are keen at detecting hidden trends. It’s more than just writing a query to pull the right information out of a database- data mining is about knowing which pieces of data should be used and when. It’s about knowing how to piece two seemingly unrelated pieces of information together to form an extremely insightful conclusion.
Like panning for gold, data mining unearths the valuable nuggets of information most critical to a company’s success. With intelligent data mining, you can easily sift through menial data and extract the reward of meaningful patterns, relationships, and discoveries that add value.
Thanks to all the participating Vedix, including:
Rajesh Kutty, iVEDiX Founder & CEO
Whether he’s designing and deploying enterprise-wide BI initiatives from scratch or integrating within an existing system, Raj has the skills to bridge gaps between solutions and the people who need to use them. Raj’s previous experience in the industry includes: Former Director of Services at arcplan Americas, Eastman Kodak’s Best Engineering Team Award, and SAP’s Global Data Warehouse Best Practices Award.
Dr. Jean Michel Guillemin Laborne, iVEDiX CIO
A passionate mathematician and data modeling genius. Jean Michel’s passion for breaking down complex problems and systems into the basic components needed to create a solution is second to none. Prior to joining the team at iVEDiX, he was Kodak’s Chief Data Architect. Here he honed his skills designing award-winning models and solutions for a multitude of teams throughout Kodak.
Jim Daily, iVEDiX Solutions Architect
Jim is a recent Rochester Institute of Technology graduate with a Masters in Information Technology. He has a passion is for finding elegance inherent within a database structure and communicating that through the data model. Jim’s goal is to constantly improve his skills in application development and the art of data modeling.
Nathan Polselli, iVEDiX Solutions Architect
An RIT grad constantly pursuing the perfect blend between business and technology. He uses his Information Technology and Economics background to provide customers with the most effective and optimized solutions possible. Quick to learn new techniques and technologies, Nathan jumped in with both feet to learn our partners’ systems. His goal is not only to use them effectively, but also to get superior results for our customers.
Ashley Fantigrossi, iVEDiX Director of Marketing Communications
With a background in consumer electronics and telecom, business intelligence is a new front for exploration in the mist of this marketer’s communications expertise. Alumna of Alfred University’s College of Business, School of Art & Design, and Women’s Leadership Academy, Ashley casts a dedicated vision for team collaboration and iVEDiX’s strong visual brand.