In an ever more dynamic and fast-paced business environment, today’s intelligence requirements are changing dramatically. Decision-makers need to capture and make sense of massive amounts of data generated by an increasingly diverse array of sources ranging from email servers to smart phones. They also need to act on information quickly – within hours or even minutes. In this swiftly moving information ecosystem, the large-scale database and business intelligence projects of yesterday are proving too costly, too complicated and too slow to keep up.
Faster, cheaper and simpler is the new analytics paradigm, and approaches that take advantage of the cost savings and flexibility enabled by open source are moving to center stage. Here’s how I see the analytics and BI landscape evolving in 2010 and beyond, and what businesses should consider as they prepare for open source.
Putting Intelligence on the Fast Track
Current business decision cycles are far more urgent than they used to be. Churning out quarterly revenue reports are no longer enough for organizations that need to act on what happened yesterday, an hour ago or minutes ago to optimize online marketing campaigns, identify security threats, maximize efficiency and effectively allocate resources. But this need for speed is complicated by the fact that businesses must collect, track, analyze and store more information than ever before. The challenge is this: How can businesses transform terabytes of data – everything from clickstream data, event logs, customer information and more – into intelligence fast enough for it to deliver value?
Business units simply don’t have time to go through protracted IT review and delivery processes to get the answers they need. This is where open source offers a big advantage. As the development model has evolved, there are now many open source projects focused on analytics, BI, data integration and data management activities. With options that are easy to deploy, simple to use and free to download in minutes, organizations can test-drive new tools without risk and get projects up and running quickly without the need for specialized IT skills.
For instance, when I was executive vice president of worldwide sales at MySQL, my organization urgently needed to make key decisions that required timely analysis of incoming data spanning lead quantity, quality and conversion rates and other indicators that delivered important insight into sales effectiveness. Our central IT department was tied up with a host of other priorities – such as making changes to the enterprise resource planning system, managing the network and dealing with email systems – and couldn’t deliver the answers we needed fast enough. Instead of waiting for central IT, we built a departmental data mart by layering a BI tool on top of our open source database platform. This framework enabled us to fulfill our immediate reporting needs without having to go through a lengthy service level agreement process. The flexible nature of the solution also gave business users the ability to incorporate new queries on a daily and weekly basis in order to get the insight that was required to run such a dynamic business.
This example mirrors what goes on in all types of businesses today. Organizations need simple tools and technologies that can either help central IT respond as fast as business needs demand or give business units an easy way to do it themselves.
Democratize Access with Affordability
Most commercial database, analytics and BI solutions require custom configuration and maintenance, expensive licensing agreements and a massive hardware footprint. An option mainly for large Fortune 500-type organizations with deep pockets, these kinds of tools leave midsized and smaller businesses out in the cold. Yet today, businesses of all budgets and sizes require rapid-fire data analysis.
According to a December 2009 report on open source by The 451 Group, a survey of 1,700 users revealed that cost savings are a primary driver for adopting open source software, and current economic conditions are contributing to increased interest in open source. The report shows that open source software is meeting or exceeding cost savings expectations for users nearly 90 percent of the time.
This finding is not surprising – open source products are either free or a fraction of the cost of their proprietary counterparts. In the analytics and BI arena, this means that companies that previously didn’t have the budget for costly software, hardware and an army of database administrators to manage it all can now get in the game. And in the face of slashed technology budgets, even larger companies are benefiting from affordable open source alternatives. But it shouldn’t take an economic downturn to convince organizations to give open source a try. With ROI surpassing expectations in many cases and usage moving into the mainstream, open source is poised to become the rule rather than the exception.
Simplicity and Flexibility Support Change
The highly dynamic nature of business in a Web 2.0 world not only demands fast analysis of big data, but also the ability to run ad hoc queries that marry multiple streams of data from many diverse systems and sources. Valuable information is being generated by a host of devices beyond traditional transactional systems, including smartphones, Web servers, e-readers, Xboxes and GPS systems. As these new sources of data flow into the information ecosystem, the questions that need to be answered about customer behavior are constantly changing. For example, today an online retailer may need to know how many purchases resulted from a new mobile marketing campaign. Tomorrow, the same company may want to understand how their brand is discussed on social media sites like Twitter.
Open source lends itself to flexibility and ease of use. In fact, the December 2009 report from The 451 Group cites flexibility as the biggest post-adoption benefit experienced by the users surveyed. Because most open source software is standards-based, tools are usually compatible with a broad set of operating systems and easily integrated with existing systems and data sources. What does this mean for analytics? As new data sources become relevant or new query and reporting requirements are added to the mix, open source can help organizations quickly accommodate end-user demands without requiring the intervention of specialized resources. It’s a case of simplicity and flexibility winning out over more complex and rigid approaches. Change doesn’t have to mean painful IT overhaul.
Preparing the Way
As open source development continues to mature, the benefits of giving innovative applications and tools a try far outweigh the risks. But before jumping in, consider a few key factors:
1. When it comes to evaluation, treat open source software as you would any other type of technology product. Although many open source tools can be downloaded and deployed in minutes, it’s important to perform your due diligence: Does the software have all the features your organization requires? Is it stable? Does it deliver the performance required? Will it integrate well with other deployed solutions and sources?
2. There’s more than one flavor of open source, and it’s important to understand the difference. As the open source model has matured, software development projects now fall within two major categories: community open source and commercial open source. Community open source software is always free, and development is carried out by the community of users. Because these kinds of projects are not designed on a for-profit model, there’s more of a do-it-yourself aspect involved when it comes to maintenance, upgrades and support. Commercial open source products are still built on open source licensed code, but they are backed by a company that also offers, for a fee, elements that are important to enterprise users such as SLAs, development resources, support and documentation. Commercial open source products may have additional features or add-ons that are commercially licensed and reserved for paying customers. Commercial open source software is a good option for users that require business-level service but who still want to take advantage of the affordability and flexible development options enabled through the model. At the same time, community offerings are a great way to try out new applications and tools with zero financial risk, and to experiment with features and functionality before committing to a license.
3. Consider an incremental approach. There’s no need to rip out existing deployments that required a good deal of time and effort to design and customize. A great way to get started with open source is to target emerging requirements or gaps in the BI landscape. Once those projects prove successful, additional needs can be met with open source incrementally.
The rise of open source complements the evolving analytic requirements of modern businesses. With access to open source alternatives that address the challenges of extracting value from data in a complex new world, organizations can explore faster, cheaper and simpler paths to business insight.
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