Market conditions are changing quickly; firms need to make the best possible business decisions at the right time and base them on timely, accurate, and relevant information from business intelligence (BI) solutions. The repercussions of not handling BI change well are especially painful and may include lost revenue, lower staff morale and productivity, continued proliferation of shadow IT BI applications, and unwanted employee departures. Ineffective change management often lies in the process of preparing the people affected by change rather than in planning the technology implementation. Firms that fail to prepare employees for enterprise BI change early enough or well enough will be left behind. They need to implement a multifaceted series of activities ranging from management communication about why change is needed to in-depth, role-appropriate employee training.
Why change management is so critical? Most strategic business events, like mergers, are high-risk initiatives involving major changes over two or more years; others, such as restructuring, must be implemented in six months. In the case of BI, some changes might need to happen within a few weeks or even days. All changes will lead to either achieving or failing to achieve a business result. There are seven major categories of business and organizational change:
Business process changes
New technology implementations
Changes to business process outsourcing or IT sourcing
Initial business intelligence (BI) ployment efforts are often difficult to predict and may dwarf the investment you made in BI platform software. The effort and costs associated with professional services, whether you use internal staff or hire contractors, depend not only on the complexity of business requirements like metrics, measures, reports, dashboards, and alerts, but also on the number of data sources you are integrating, the complexity of your data integration processes, and logical and physical data modeling. At the very least Forrester recommends considering the following components and their complexity to estimate development, system integration and deployment effort:
Rowan Curran, Research Associate and TechnoPolitics producer, hosts this episode to ask me (your regular host) about The Pragmatic Definition Of Big Data. Listen (5 mins) to hear the genesis of this new definition of big data and why it is pragmatic and actionable for both business and IT professionals.
Podcast: The Pragmatic Definition Of Big Data Explained (5 mins)
As John Brand and I recently wrote, business intelligence (BI) adoption drivers, technology understanding, and organizational process maturity continue to vary widely across Asia Pacific (AP). But there is one constant in this market: the regularity with which BI appears at or near the top of CIOs’ priority lists.
While the gap between global best practices and regional implementations is closing, social, cultural, economic, and underlying technology trends will continue to affect BI adoption in the region for the foreseeable future:
Social. The adoption of social computing is expanding rapidly across all AP markets, but is particularly strong in growth markets like China, Indonesia, and the Philippines. As in North America and Western Europe, this adoption is already having profound effects on how organizations identify, understand, and engage with customers and other market influencers. But the lack of significant BI investments means that organizations in these growth markets are far more likely to consider issues like sentiment analysis, predictive analytics, and near real-time data access when sourcing initial BI projects.
In a recent media interview I was asked about whether the requirements for data visualization had changed. The questions were focused around whether users are still satisfied with dashboards, graphs and charts or do they have new needs, demands and expectations.
Arguably, Ancient Egyptian hieroglyphics were probably the first real "commercial" examples of data visualization (though many people before the Egyptians also used the same approach — but more often as a general communications tool). Since then, visualization of data has certainly always been both a popular and important topic. For example, Florence Nightingale changed the course of healthcare with a single compelling polar area chart on the causes of death during the Crimean War.
In looking at this question of how and why data visualization might be changing, I identified at least 5 major triggers. Namely:
Increasing volumes of data. It's no surprise that we now have to process much larger volumes of data. But this also impacts the ways we need to represent it. The volume of data stimulates new forms of visualization tools. While not all of these tools are new (strictly speaking), they have at least begun to find a much broader audience as we find the need to communicate much more information much more rapidly. Time walling and infographics are just two approaches that are not necessarily all that new but they have attracted much greater usage as a direct result of the increasing volume of data.
Cloud Services Offer New Opportunities For Big Data Solutions
What’s better than writing about one hot topic? Well, writing about two hot topics in one blog post — and here you go:
The State Of BI In The Cloud
Over the past few years, BI business intelligence (BI) was the overlooked stepchild of cloud solutions and market adoption. Sure, some BI software-as-a-service (SaaS) vendors have been pretty successful in this space, but it was success in a niche compared with the four main SaaS applications: customer relationship management (CRM), collaboration, human capital management (HCM), and eProcurement. While those four applications each reached cloud adoption of 25% and more in North America and Western Europe, BI was leading the field of second-tier SaaS solutions used by 17% of all companies in our Forrester Software Survey, Q4 2011. Considering that the main challenges of cloud computing are data security and integration efforts (yes, the story of simply swiping your credit card to get a full operational cloud solution in place is a fairy tale), 17% cloud adoption is actually not bad at all; BI is all about data integration, data analysis, and security. With BI there is of course the flexibility to choose which data a company considers to run in a cloud deployment and what data sources to integrate — a choice that is very limited when implementing, e.g., a CRM or eProcurement cloud solution.
“38% of all companies are planning a BI SaaS project before the end of 2013.”
Earlier this week Dell joined arch-competitor HP in endorsing ARM as a potential platform for scale-out workloads by announcing “Copper,” an ARM-based version of its PowerEdge-C dense server product line. Dell’s announcement and positioning, while a little less high-profile than HP’s February announcement, is intended to serve the same purpose — to enable an ARM ecosystem by providing a platform for exploring ARM workloads and to gain a visible presence in the event that it begins to take off.
Dell’s platform is based on a four-core Marvell ARM V7 SOC implementation, which it claims is somewhat higher performance than the Calxeda part, although drawing more power, at 15W per node (including RAM and local disk). The server uses the PowerEdge-C form factor of 12 vertically mounted server modules in a 3U enclosure, each with four server nodes on them for a total of 48 servers/192 cores in a 3U enclosure. In a departure from other PowerEdge-C products, the Copper server has integrated L2 network connectivity spanning all servers, so that the unit will be able to serve as a low-cost test bed for clustered applications without external switches.
Dell is offering this server to selected customers, not as a GA product, along with open source versions of the LAMP stack, Crowbar, and Hadoop. Currently Cannonical is supplying Ubuntu for ARM servers, and Dell is actively working with other partners. Dell expects to see OpenStack available for demos in May, and there is an active Fedora project underway as well.
In the latest evolution of its Linux push, IBM has added to its non-x86 Linux server line with the introduction of new dedicated Power 7 rack and blade servers that only run Linux. “Hah!” you say. “Power already runs Linux, and quite well according to IBM.” This is indeed true, but when you look at the price/performance of Linux on standard Power, the picture is not quite as advantageous, with the higher cost of Power servers compared to x86 servers offsetting much if not all of the performance advantage.
Enter the new Flex System p24L (Linux) Compute Node blade for the new PureFlex system and the IBM PowerLinuxTM 7R2 rack server. Both are dedicated Linux-only systems with 2 Power 7 6/8 core, 4 threads/core processors, and are shipped with unlimited licenses for IBM’s PowerVM hypervisor. Most importantly, these systems, in exchange for the limitation that they will run only Linux, are priced competitively with similarly configured x86 systems from major competitors, and IBM is betting on the improvement in performance, shown by IBM-supplied benchmarks, to overcome any resistance to running Linux on a non-x86 system. Note that this is a different proposition than Linux running on an IFL in a zSeries, since the mainframe is usually not the entry for the customer — IBM typically sells to customers with existing mainframe, whereas with Power Linux they will also be attempting to sell to net new customers as well as established accounts.
Join us at Forrester’s CIO Forum in Las Vegas on May 3 and 4 for “The New Age Of Business Intelligence.”
The amount of data is growing at tremendous speed — inside and outside of companies’ firewalls. Last year we did hit approximately 1 zettabyte (1 trillion gigabytes) of data in the public Web, and the speed by which new data is created continues to accelerate, including unstructured data in the form of text, semistructured data from M2M communication, and structured data in transactional business applications.
Fortunately, our technical capabilities to collect, store, analyze, and distribute data have also been growing at a tremendous speed. Reports that used to run for many hours now complete within seconds using new solutions like SAP’s HANA or other tailored appliances. Suddenly, a whole new world of data has become available to the CIO and his business peers, and the question is no longer if companies should expand their data/information management footprint and capabilities but rather how and where to start with. Forrester’s recent Strategic Planning Forrsights For CIOs data shows that 42% of all companies are planning an information/data project in 2012, more than for any other application segment — including collaboration tools, CRM, or ERP.