Big Data, Analysis and Business Intelligence
There is a lot of talk among IT professionals of “big data”, and discussions at many business conference tables center on how the organization might find greater benefit and advantage from the intelligence buried in the business systems and information. It is a two-part problem, where the collection and the analysis each play essential roles in developing real business intelligence.
“So what’s getting ubiquitous and cheap? Data.
And what is complementary to data? Analysis. ..”
Hal Varian, Chief Economist at Google and emeritus professor at the University of California, Berkeley
“Hal Varian Answers Your Questions,” February 25, 2008 (http://www.freakonomics.com/2008/02/25/hal-varian-answers-your-questions/). BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT; MIS Quarterly Vol. 36 No. 4, pp. 1165-1188/December 2012
The information technology and systems in a business support the operation. Software and computers help people do their jobs, and the information collected in and generated by those systems becomes the foundation for developing business “intelligence”. Today, businesses must reach beyond their own direct operational support systems and consider the full realm of data to be collected, including IoT sensor data or social media data.
Business intelligence is gained from the analysis of the critical business data – analysis which helps owners and managers make better and more informed decisions which are based on an understanding of the business and market. Business intelligence was a term popularized in the 1990s, but the key was the analytical component (business analytics), which gained focus in the late 2000s. Today it is big data and big data analytics, where organizations are working with massive data sets not previously even imagined.
“…one of the most significant challenges facing enterprise IT teams today is how to efficiently support and enable the “science” of big data, while providing the confidence and maturity of more traditional (and often better understood) infrastructure services.”
http://www.datacenterknowledge.com/archives/2015/05/26/hadoop-big-data-storage-challenge-overcoming-science-project/
The volume and velocity of information collection is ever-increasing even in the smallest of businesses, creating a great need for tools which can structure and correlate data so that it might render some insight. Simply storing and managing these huge and growing data sets has become a challenge, and there isn’t one right way.
Once the business has the data, then it must find a way to analyze the data, which generally involves also applying visualization tools. Many IT departments are feeling pressured in the development of new skills and capabilities around data collection and management, yet it is more frequently the business user who provides the analysis and applies visualization tools to the task.
“Data collected by the Aberdeen Group, found that employees in organizations that used visual data discovery were more likely to find the information they need, when they need it. These same companies were able to scale their use of scarce IT skills more effectively.”
http://www.tableau.com/learn/whitepapers/visualization-set-your-analytics-users-free#0vXrkWZbizxyutw
The use of business intelligence and advanced analytics continues to grow in every segment of the market – from small business to enterprise – and plays an increasingly important role in supporting business success.
Until this point, most businesses didn’t have the technology or the data to enable significant quality or business transformation, but the times are changing and deployments of data collection, analysis and visualization software and tools are expanding with it. This is a fundamental aspect of business digital transformation and fuels the next step, where intelligence is applied to conditions revealed in the data and activities are automatically performed guided by that intelligence.
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Manufacturing, particularly custom manufacturing or ETO (engineering to order) is among those industry types that could benefit tremendously from a more intimate and detailed approach to accounting. Unfortunately, it is often difficult to find experienced professionals with not simply a competence in working with manufacturing industry sector clients, but specifically with ETO process. Building to order is one thing, but finding the way to improve efficiency and profitability when every job is a custom encounter takes additional skills and a lot of data.
On the other hand, there are professionals who recognize that a proactive approach to helping clients results in better and richer client engagements and better-performing client businesses. These professionals are truly the business advisors to the client – the trusted partners who understand the variety of conditions which impact business performance and care to make sure they are properly addressed. This advisor not only reports but makes recommendations and provides guidance on certain situations or processes which are essential in the business model. These professionals recognize that the bookkeeping and operational information collection is not simply a means to an end; these professionals understand that these foundational processes and the information they encompass are the important details which reflect the true performance of the business… details which no summary report can fully describe.
I’m a little concerned, and any professional in accounting and finance who works with small businesses should be just a little concerned, too. Why? Because there is a belief out there that some nifty software and Internet Of Things (IoT) approach to finance will ultimately eliminate the need for a small business to work with skilled, trained accounting professionals. Remember the marketing slogan introduced by Intuit with QuickBooks – the one that suggested that, “if you can write a check, you can do your own books”? Most accountants will tell you that it is not true, and the ability to operate a product like QuickBooks does not magically turn poor accounting and bookkeeping information into good business data. In fact, it most frequently enables
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