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What is Hot in Business Intelligence for 2010 and Beyond

by William Laurent, William Laurent, Inc.Monday, January 4, 2010

I continue to be very excited and encouraged by recent developments in enterprise business intelligence.  Despite a recent global downturn in software sales, many BI dashboard vendors and solutions providers, both large and small, have aggressively accelerated their pace of innovation and service offerings.  Over the last year, I was fortunate enough to meet with the leaders behind some of the more cutting-edge BI solutions and discuss in detail their company’s unique vision and value proposition for BI.  What impressed me about these companies was not only the innovative quality and value (functionality/price) of their solutions portfolio, but the industry thought leadership that emanated from their senior management.  The business intelligence industry continues to retain a brilliant knowledge-trust that is bent on breaking new ground in BI and transforming it for the better.


GoodData has drastically lowered the barrier of entry into business intelligence by providing a cloud-based service that is scalable, flexible and affordable.  The inspiration behind GoodData is simple: Business intelligence should no longer be viewed as a luxury good - available only to large companies with the budget to shop at the IT equivalent of a Mercedes Benz dealer.  Every company, regardless of market capitalization, must have the ability to access, analyze and report, and distribute the data (in an infinite number of permutations) on which their business runs.  And yet outside of Fortune 1000 companies, BI still has a very small market penetration.  Because of this unequal access to BI, GoodData's founder and CEO, Roman Stanek, was inspired to apply the emerging economics of cloud computing to BI service delivery, making it available to a much wider audience.

GoodData securely hosts data and gives businesses the ability to build and manage a multi-dimensional data model from a variety of data sources.  They provide their clients with the tools to analyze data in a collaborative environment and the means to share the results with others, with no costly software purchases or infrastructure overhead.  Mr. Stanek expounds, “We look at problem of scale - how can we provide real data warehousing and analytics to large number of companies without a BI team or its own data center?”

Taking advantage of the latest advancements in cloud computing and internet computing, GoodData has been able to break through common BI roadblocks.  They have done so by focusing on simple common-sense design principles. To name just a few: 

  • Users should interact with GoodData the way they interact with their enterprise applications’ data and typical online services.
  • Customers should be able to start simply, grow with their success and pay for the value of the results dynamically. They should not be bound by a monolithic and tangled architecture that will cost millions of dollars to put in place before the first row of decision-support data is ever created.
  • Business Intelligence projects should leverage agile development

As is often the case in software, such simple ideas make for an innovative solution: Now all BI data can be hosted and operated on in one common physical space.  To get their clients started on the road down cloud-based BI, they offer a CSV upload wizard for simple data files up to 10 MB (about 100,000 rows in an Excel file), making various scheduling and automation tools available so that clients are assured the most up-to-date data; REST-based APIs and pre-built scripts allow users to load data directly and securely from any location.

GoodData makes it simple, flexible and affordable to bring business data into a single online space for reporting and analysis.  Most importantly, there is no software to install, no licenses to buy and no IT support required because they are securely hosting their clients' data.  In fact, GoodData can reverse engineer data into complex data models - actually creating data models from data that is uploaded to their cloud environment, inferring models from ETL tools, spreadsheets and more.  Data modeling tools are also available that let users customize or extend dynamically any data model (whether entity-relational, dimensional, object oriented), including any attached attributes, metrics and facts.

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