Tag Archives: BI

The Self-Aided Analytics Solution

There has long been a problem in making analytics solutions available and accessible to the user. This has created innumerable trends toward simplification, and left many users with inadequate solutions. Large numbers of businesses and enterprise departments still rely upon spreadsheets to fill a significant portion of their Business Intelligence and data analytics requirements. However, the advent of Big Data and the advantages of Advanced Analytics are making simple solutions less possible and are raising the bar for analytics across all types and sizes of business.

Unfortunately, Advanced Analytics requires expertise that is not always available. While processing capabilities are becoming available on a SaaS basis from the cloud, experts are still required to formulate questions and produce understandable results. But what if we could apply Analytics to the querying process itself, and to the production of usable results?

New programs are beginning to do just that, with IBM’s Watson Analytics leading the way in providing a Natural Language Processing front-end for its Cognos analytics solution, and using analytics to provide immediately accessible visualizations to the user. All major analytics vendors are now moving in the direction of Natural Language Processing for queries, and a number of vendors are also moving into easy visualizations, as defined by market leader Tableau, that permit a naïve user to more fully grasp the implications of available data. Continue reading The Self-Aided Analytics Solution

SIIA in Boston – Deciphering Data and Analytics for ISV Business

What is Happening?

ISVs can, should, and do profit from the use of advanced data analytics – not only by integrating them within software and services offerings, but more importantly, by integrating an increasing range and scope of data (including Big Data) and analytics into their own business operations and decision making. Data regarding user behavior, operational efficiencies, and relationship management can and should be analyzed to help determine and take advantage of customer / buyer desires and needs, as well as competitive abilities, solution improvements, development strategy, upsell / cross-sell opportunities, pricing, business models, and hiring / retaining the most useful employees.

These were among the lessons reported by Saugatuck Research Fellow Bruce Guptill, who had the pleasure of attending and participating in this week’s “Deciphering the Data Storm” event, presented in Boston by the Software & Services division of the Software and Information Industry Association (SIIA).

Key lessons learned and reported by ISVs regarding the analysis and application of a wide range of business data (including Big Data) include the following:

  • Data needs “gravity” in order to be useful; i.e., data needs varying combinations of human business context, situational relevance, and environmental semantics (i.e., “the voice of the author”) in order to be qualified, let alone be useful in analysis.
  • Don’t always focus on reducing / limiting the “bigness” of data. Adding to / augmenting data with similar, complementary, and relevant data can provide and improve the “gravity” of that data. The key information sought may not be found completely in your own data. That being said, don’t be afraid to apply a variety of filters to screen Big Data; just be willing to accept failure and move on quickly when the filtering doesn’t work as expected.
  • Share data in common to improve collaboration. “Success” is defined differently everywhere, even within small ISVs. Utilizing common sets of data has more beneficial impact, and enables more and better business collaboration, than trying to develop and focus on a “single version of the truth.” Different groups will always have different perspectives, and use data in different ways; ensuring that the data used is common rather than simply absolute will enable better understanding, and foster more (and more useful) interaction.
  • Know what the next step is. In other words, set realistic business goals beyond simply analyzing data. Once deeply into the analysis, it’s easy to lose sight of business reasons behind the analysis. And as more data becomes more readily available from more sources, it becomes more and more easy to become overwhelmed.

Continue reading SIIA in Boston – Deciphering Data and Analytics for ISV Business

MicroStrategy Bundling & Pricing Spotlights Continuous ISV Cloud Business Transitions

BI software vendor MicroStrategy announced significant revisions to its offering delivery and pricing, bundling what had been 21 separate offerings into 4 “packages,” aimed respectively at developers, mobile users, power users in traditional server-based environments, and users preferring a Web-based interface. According to MicroStrategy, “clients will have all styles of analytics (self-service, dashboards, advanced analytics) across any interface (web, mobile, pdf, email report distribution) at Big Data scale–on an automated platform.”

The company’s pricing shifted somewhat to reflect the bundling. PC World reports the new pricing as follows:

In our view, this move spotlights how ISVs across all types of markets not only continue to revisit, review, revise, and refresh their offerings, pricing and delivery methods, but also how they must continually update, upgrade, and rethink not only offerings, but also practically every aspect of the company, even as they Continue reading MicroStrategy Bundling & Pricing Spotlights Continuous ISV Cloud Business Transitions

Managing Risk, Big Data Style

Although Big Data and Risk Management would seem to be a marriage made in heaven, risk management generally tends to lag in advanced analytics adoption. There are numerous reasons for this, starting with a reluctance to tamper with financial processes, and going on to the central risk management difficulty of predicting uncertain events. Big Data reluctance is seen most easily in the Insurance sector, where businesses are built upon risk management—yet practitioners are averse to using analytics tools which do not readily yield a predictive result. In fact, the debate rages on as to whether calculating risk is an art or a science, and recent advances in Big Data are only just beginning to move the needle more toward science.

The base problem is that data of a single type alone, no matter how significant the amount, cannot help much in the prediction of events outside of the data perimeter. Risk management is about estimating possible unfortunate effects and considering their possibilities and mitigation. In a limited space, such as IT alone, this is a highly simplified exercise. But, looking at the possible factors that might impact a business, the range is simply too wide, and it is difficult to even locate significant events within the data. Continue reading Managing Risk, Big Data Style

Age of the Smart Cloud: Analytics Monetization

Global systems integrators (GSIs) and other Cloud solution providers are positioning now to serve the Analytics-as-a-Service market. Many have made significant investments in attacking this nascent market for Cloud Analytics. Saugatuck Technology has been interested in developing an understanding of this emerging market and the role monetization will play. We approached four leading vendors of monetization solutions — Aria, MetraTech, SafeNet and Zuora – and requested an interview on the monetization strategies likely to emerge in the market for Analytics-as-a-Service solutions. The monetization vendors made these executives available for our interviews:

One question we asked these monetization experts to address was about “Collaborative and Collective Analytics.” Continue reading Age of the Smart Cloud: Analytics Monetization

PivotLink Summit Highlights Evolution of Cloud BI Market

What is Happening?

Saugatuck attended the PivotLink Customer & Marketing Analytic Summit this week in San Francisco. We came away from the event only further believing that an important shift is taking place in the BI industry – and, to some extent, the fast-growing Cloud BI industry segment as a whole. Continue reading PivotLink Summit Highlights Evolution of Cloud BI Market

Cloud-based BI / Analytics: A Top-Growth Business App Through 2013

What is Happening?

While interest and hype surrounding Cloud-based analytics and BI solutions today are ahead of today’s actual rate of adoption, adoption is about to catch up to and pass the hype level.

Saugatuck’s 2012 research and analysis shows that, as of YE 2011, only about 13 percent of enterprises worldwide – including all industries and all sizes of enterprises – indicated that they had Cloud-based BI/advanced analytics solutions in place and in use.

But that same research shows that Cloud-based BI and analytics will be among the fastest-growing Cloud-based business management solution types through at least 2013. Figure 1 summarizes our survey data and analysis regarding Cloud-based business management solution adoption and usage growth through 2013 – and shows how Cloud-based BI / Advanced Analytics forecasts an 84 percent compound annual growth rate (CAGR) over this period.

Figure 1: BI and Cloud Business Solution Use and Relative Growth, 2011 – 2013

Business Management Applications Categories Survey Saugatuck
Source: Saugatuck Technology Inc., 2012 global SaaS survey; n = 228

Continue reading Cloud-based BI / Analytics: A Top-Growth Business App Through 2013

The Role of Sensor Data in the Boundary-free Enterprise™

What is Happening?

Cloud, Mobile, and Social applications have competed for their places in the enterprise over the last few years. Now that these interrelated applications have emerged as part of the new master architecture, which Saugatuck has termed the Boundary-free Enterprise™, we believe that businesses will be able to refocus their IT teams to expand business capabilities, rather than concentrating so much of their time on renovating and maintaining existing systems (1054RA, The Emerging Master IT Architecture – Client / Server Gives Way to CMSA, 12 April 2012). We expect sensors and sensor data generated from real-world conditions and activities will be leveraged to enable IT departments to deliver real-time business value, and will make an important part of the expanding business and IT capabilities in this new Master Architecture. Continue reading The Role of Sensor Data in the Boundary-free Enterprise™

Some New Intel on Business Intelligence (BI)

In the course of our everyday work, Saugatuck researchers regularly review information and insight developed by third parties – after all, a worldview limited to one’s own data and insights is necessarily incomplete.  One of the more interesting sets of intel and insights we’ve seen comes from old friend Howard Dresner of Dresner Advisory Services, who has published a very helpful analysis of what’s shaping Business Intelligence (BI) adoption and use worldwide.

The highlights that we found most illuminating included the following:

1. BI is a group-oriented/department-oriented phenomenon for the most part. While there are still some “top-down,” enterprise-wide efforts going on, the core market growth is user-, department-, and application-driven BI, addressing specific issues/opportunities/problems. That suggests the possibility for fragmentation (and high TCO) within enterprises pursuing multiple, non-coordinated BI initiatives – unless they are building on open-source solutions (see below). The groups most likely to drive BI projects? Finance and Marketing – no real surprise there, but very useful to know, especially if you’re a solution provider, or an IT manager trying to find where next year’s budget will be spent.

2. BI implementation project numbers overall are slowing, while spending is increasing – implying that many existing projects may be getting more investment. To our mind, that’s good news; enterprises may finally be moving beyond trial stages or the single-task stage, and building out to more efficient and effective BI capabilities. The data also suggest that “big bang” projects are declining in numbers, which suggests that the remaining spending is on smaller, group- and function-specific BI.

3. Open source BI providers have significant potential to be disruptive to traditional BI markets and players, as the data suggests that they tend to be coming from outside IT; they tend to be deployed in smaller groups by younger (more tech/Cloud-savvy) users; and user organizations relying on commercial open source-based BI tend to settle on the solutions they have, and not utilize other BI providers as much as their traditional enterprise counterparts do. An important factor we found in the report is that, as with almost all open source solution adoption today, BI users tend to begin with free “community” editions and build those out as much as possible before even considering the use of more powerful and capable “commercial” editions. So at least some of the perceived loyalty to open source may be grounded in users’ desire to not spend money on software.

The bottom line? A growing number of group-oriented and function-oriented BI projects, with a significant open source base, suggest a growing need for VARs, SIs and Cloud-based providers to deliver BI integration services and solutions. If enough of these projects bear enough fruit and get incorporated into enterprise business planning and management, there will be massive demand for integration services within the next few years.

Check out the report and more information at BusinessIntelligenceInsider.com. You will need to become a site member to access the research.