Is a ‘Big Data’ Degree Really Worth It?

Is a ‘Big Data’ Degree Really Worth It?

It was bound to happen sooner or later — degrees that didn’t exist 20 years ago because of the advancement, and wonders of, modern-day technology. No, we’re not quite at the point of a Masters in Self-Driving Car Engineering (more to come here when Google perfects their machines in that department). But the need for data-driven decisions in organizations has given way to a ton of degrees capitalizing on this analytical bar being raised. In fact, according to Paul Barth, co-founder and CEO of Podium Data, in a recent BostInno article, “in recent years, the number of Master’s programs in data science has grown from a mere handful to more than 170.” And just running a simple search shows the explosion of these programs, from quite the esteemed list of colleges and universities: NYU: Master of Science in Data Science Columbia University: Master of Science in Data Science Bentley University: Masters in Marketing Analytics Stanford University: M.S. in Statistics – Data Science Michigan State University: MS in Business Analytics  These are some well-respected institutions of higher learning, no doubt. The question is, is the esteem still worth the investment? It Depends There’s opportunity for both the less technical employee, and the one with the advanced degree, according to Aberdeen Group VP & Principal Analyst, Analytics & Business Intelligence, Michael Lock. Whether or not you should make a big — and costly — investment in a Masters in Data Science is something that’s completely dependent on the organization in which you plan to work. “With more sophisticated data capture and processing capabilities today, the opportunities could be even greater for the more data-savvy users,” said Lock, with...
Insight for Infrastructure: BI Takes Hold in the Public Sector

Insight for Infrastructure: BI Takes Hold in the Public Sector

Many of us are still relatively sheltered from the world of Big Data, regardless of how much we may gripe about how many emails clog our inboxes. Compare that fairly common perspective with that of an energy grid operator who measures and meters power consumption for millions of homes, or perhaps a local Department of Transportation and their efforts to maximize toll revenue, while minimizing traffic and congestion. Between the people, processes, and systems involved in the world of critical infrastructure, and the volume of data generated, it quickly becomes apparent just how massive the challenge can be, and how enticing the opportunity is. According to Aberdeen Group’s recent 2015 Business Analytics survey, organizations in the public sector are driven toward a more formal data management and analytical strategy for three main reasons: Data is too spread out and inaccessible. The complexity of data inherent to this industry would be daunting to even the most data-savvy and technically advanced. Energy and infrastructure organizations manage a bevy of information, from traditional structure application-generated data to potentially thousands of individual devices spewing out real-time sensor data. It can be hard enough to simply access the necessary data, let alone do anything useful with it. Competitively, analytics is no longer a “nice to have.” The world of business intelligence and analytics has evolved quickly, if somewhat predictably. Where the occasional canned report or dashboard was once sufficient, companies are now looking to get more active in the analytical process. Moreover, that level of increased activity and engagement would have once been a competitive advantage for companies, but now is considered table stakes (at least in...
Five Secrets to Turning Big Data Into Fast Data

Five Secrets to Turning Big Data Into Fast Data

Organizations today realize that it’s a double-edged sword when dealing with Big Data — not only is there a lot of it flying into the business at a feverish pace, but it is more complex than ever before, especially as the business scales. And as if it were enough to just deal with this growing volume and complexity, with tight decision windows, business leaders are expected to hasten this decision process and make sense of this influx of data faster than ever before. We realize you’re not Superman (if you are, you’ve got bigger things to worry about), so we’ve got you covered in these five secrets to turning Big Data…into fast data, through effective data management and integration. For a bonus sixth secret, be sure to check out the full checklist, Six Secrets of Accelerated Data Integration, available 100% free of charge to registered Aberdeen community members.  And for even more on the subject, read the full research report, Big Data Becomes Fast Data with Accelerated...
Small Companies Exploit a Tight-Knit Analytical Community

Small Companies Exploit a Tight-Knit Analytical Community

According to the most recent census data, firms employing fewer than 100 people constitute 98% of the nearly 6 million companies in the U.S. Moreover, these small companies employ more than 42 million Americans. Often referred to as “Mom and Pop Shops,” these companies face the same kinds of challenges as larger enterprises, albeit on a far smaller scale. They need to maintain and grow their customer bases, reduce waste and drive more process efficiency, and boost brand visibility and increase their market presence. Companies large and small gravitate toward business analytics as a tool to help bridge the gap and satisfy those needs. For starters, small companies look to shore up their data and find better ways of sharing critical information across business functions. Prior Aberdeen Group research demonstrated the top three analytical strategies for these small firms: Identify key data sources required for analysis – (41% of respondents) Enable decision-makers to be more self-sufficient with analytical capabilities – (37% of respondents) Improve cross-department collaboration by breaking down information silos – (30% of respondents) This three-pronged strategy makes analytics more accessible and pervasive throughout the organization. Small firms typically have a number of employees wearing multiple hats, and taking on a variety of different responsibilities. These are the very users that can exploit the potential of analytics and spread its value to other areas of the company. Small companies have inherently less complexity in their data environments, which enables them to prioritize which data sources matter the most. Because of the multi-faceted nature of many of the employees, they can transfer knowledge more effectively and empower a greater degree of self-sufficiency...
Data to Insight: Does the Education Sector Make the Grade?

Data to Insight: Does the Education Sector Make the Grade?

Whether student performance is a determinant of public fund allocation, or a leading indicator of school ranking and public perception, public sector organizations often live and die by their ability to measure, manage, and improve this key metric. In these situations, where efficiency is at a premium and data is the only plentiful asset, many organizations in the business world turn to business analytics, and the public sector has been quick to follow suit. According to Aberdeen Group’s recent 2015 Business Analytics survey, public sector organizations are driven toward analytics and data-driven decisions for three main reasons: Fragmented data. Educators across the country are realizing that the most important insights about their students and the operation of their institutions is rarely, if ever, dependent upon data from just one source, or area of the organization. Effective analytics can bridge the gap between different types of heterogeneous data and help create new forms of insight. User demand. While there may be higher demand than ever for business analysts and data scientists, the greatest need for analytical capability is often in some of the least traditional roles within the organization. From financial managers to school administrators, a new crop of job roles and user types has emerged to demand better data-driven decisions. Competitive necessity. Once upon a time, the ability to create an accurate and timely report or dashboard would have been deemed a competitive advantage. Nowadays, that level of analytical activity has become table stakes in the public sector. These organizations are driven to analytics out of a need to simply remain competitive, rather than surpassing the competition. With these pressures in mind, Aberdeen’s...
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