Business Intelligence Trends 2013: The Breakthrough of Do It Yourself BI and the Breakup of Big Data
by Markus Gisske
arcplan recently examined the trends that will shape the BI landscape in 2013 – self-service BI, collaboration, and mobile BI. Under the umbrella of Do It Yourself BI (DIY BI), these trends will come to the forefront and big data will lose steam. It might be controversial to say, but we have our reasons.
Enterprises are demanding an increased focus on cost reductions and customer profitability – typically under business users’ purview – which constantly impacts the development of BI as business users are driving future trends. In 2013, business users will demand easier ways to access and analyze data, pushing their employers to purchase the self-service tools that BI vendors have been developing over the past few years and leading to a true breakthrough of DIY BI. Beyond that, the big data challenge has not yet been solved with an easy-to-digest solution, causing a lot of the hype to die down next year (for good reason). Let’s examine these trends further:
DIY BI Part I: Self-Service BI
In the past, BI was limited to a few expert analysts and users in the IT department. No doubt it has come a long way since. More and more BI users are taking over tasks traditionally dominated by IT developers, such as report development, dashboard creation, and ad-hoc reporting. In fact, Forrester Research advocates that 80% of BI tasks should be in the hands of business users themselves – and these business users need easy-to-use interfaces, programming-free BI app creation, the ability to search, write-back and drill-down, and data exploration capabilities.
In 2013, the delays associated with IT will be brushed aside in favor of the speed, control, and rapid access that comes along with self-service BI. The demand will increase for modern ad-hoc tools that allow users to directly tap the corporate data warehouse and provide a high degree of flexibility to slice-and-dice the data for insight on the fly. In-memory technology, advanced visualizations, and the broader emergence of HTML5 will support developers in creating multifaceted web-based apps that run on any device via a standard web browser and offer simple, intuitive self-service features every type of user can enjoy. Users will become more self-sufficient in 2013, able to get the information they need in order to optimize and accelerate their decision making processes.
DIY BI Part II: Collaboration
Why I’m Not Impressed With Your Big Data
by Tiemo Winterkamp
Musings on the challenges of big data in a year of serious hype
There’s a reason you haven’t heard more than a handful of big data success stories in 2012. Handling big data correctly is hard, requires huge infrastructure and resource investments, and may not be worth it…yet. According to one survey in November 2012, 60% of businesses said it’s too early to tell if their big data project was successful and produced a proper ROI. It seems that so much of the hype around big data is focused on the technologies you need to buy and the talent you need to acquire (data scientist is the latest fad title), and not on what’s most important: what you can do with the data, what value you can extract, what business decisions you can speed up or improve with all that data.
With companies jumping on the big data bandwagon to the tune of $28 billion this year, it’s time to discuss why it might be best to ignore the hype for now and focus on reaping insight from the data you have already. Here’s why I’m not impressed with your big data:
You don’t actually have big data.
The marketing hype can lead you to believe you have a “big data problem” when you really don’t. Using the terminology incorrectly has the potential to harm your business, causing you to invest in unnecessary infrastructure when you may be able to leverage what you already have in place. Even Microsoft and Yahoo! have made this mistake…
Careers in Business Intelligence: What Makes BI an Attractive Field
by Monique MorganAlong with the demand for big data, better data, and the need for greater insight into company operations comes the need for analytic professionals who can effectively leverage this data to maximize business benefits. But it’s not always easy to find and hire these types of people. Within the past few years, we’ve seen titles such as BI Analyst, Data Analyst, Data Scientist, and Big Data Engineer emerge in job listings as companies seek out much-needed expertise to wrangle their growing amounts of information. As a matter of fact, McKinsey and Company’s often-quoted 2011 report on big data predicted that by 2018, the US alone faces a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts to analyze big data and make decisions based on their findings. The bright side of this situation is that job seekers with analytic talent and business acumen have a tremendous opportunity to make a positive impact for business teams. BI is a growing field that shows no signs of slowing down, so let’s take a closer look at what makes it attractive to job seekers as well as students deciding what course of study to pursue.
Invest in Good Data Before Big Data
by Dwight deVera
Big data is without a doubt 1 of the top 5 BI trends of 2012. The hype around big data has driven many companies to hoard massive amounts of structured and unstructured information in the hope of unearthing useful insight that will help them gain competitive advantage. Admittedly, there is significant value to be extracted from your company’s growing vault of data; however it is data quality – not necessarily quantity – that is your company’s biggest asset. So here are 3 reasons why you should devote more of your IT budget to data quality:
1) Because good data quality sets the stage for sound business decisions.
Sensible business decisions should be based on accurate, timely information coupled with the necessary analysis. Decision-makers need to be equipped with facts in order to plan strategically and stay ahead of the competition – and facts are entirely based on having correct data. Though it’s not as “sexy” as big data, mobile BI, or cloud, data quality should be the foundation of all of these other initiatives.
Admittedly, achieving data quality is tough. Gartner analyst Bill Hostmann says, “Regardless of big data, old data, new data, little data, probably the biggest challenge in BI is data quality.” It crosses department lines (both IT and business users must take responsibility), and processes that have multiple levels of responsibility often suffer from the “everyone and no one is responsible” conundrum. It’s also a complex process that requires laying out common definitions (what is a customer, what are our conventions for company names – Inc. or no Inc. – for example), performing an initial data cleanse, and then keeping things tidy through ongoing data monitoring, ETL, and other technologies.
But ensuring that your data is timely, accurate, consistent, and complete means users will trust the data, and ultimately, that’s the goal of the entire exercise if you see this first reason as the most important. Trusting the data means being able to trust the decisions that are based on the data. Clean up the data you have in place, then you can move on to a strategy that incorporates additional sources of big data.
2) Because you have to.
When Analytics and Collaboration Intersect
by Tiemo Winterkamp
Fueled by the big data hype and the need to extract greater business value from data, investment in business analytics software is on the rise. Many companies have begun to tap into the potential of big data analytics and this number is predicted to increase according to recent reports by the International Data Corporation (IDC). IDC forecasts that the market will continue to grow at a 9.8% compound annual growth rate through 2016 to reach $50.7 billion. Perhaps to a less aggressive extent, interest in Collaborative BI is also on the rise, with top performing companies incorporating collaborative techniques to share knowledge throughout the enterprise according to Aberdeen’s extensive 2011 research report on Collaborative BI. The demands for agile insight and self-service are changing the landscape of BI, driving the need for Collaborative BI, which uses social functionality to improve business decision-making. Separately, the benefits of deploying analytical tools and taking advantage of collaborative techniques are appealing for any organization seeking streamlined operational success – but the payback of merging these initiatives could be even more rewarding.
Analytics is gaining traction in the BI arena due to the need to explore massive amounts of varied information (what we now call big data), extract valuable insight, and quickly deliver these insights to the users who need it. Initiatives geared toward improving analytics utilize technology that gathers and organizes data from disparate data sources and provides a platform for in-depth analysis, yielding benefits such as improved business operations and agility, increased sales, and lower IT costs. So it’s no wonder that organizations are making significant investments in the analytics market.
Collaborative BI, on the other hand, seems to be the new kid on the block…
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