Until very recently I have spent most of my consulting career designing and constructing tactical Business Intelligence (BI) tools for Business Users sometimes with the co-operation of the IT Department and sometimes in direct competition to them. Because of this I have been cautious when investigating the new trend of Self Service BI which claims to provide a complete solution to the business user by providing advance visualization, data discovery and integration and visual analytics.
Sat at home one evening recently I was pondering over the problems that face both the IT Department and the Business User when searching for the truth amongst the myriad sources of information prevalent within most organizations. In the office a request to search for information requires the business user to submit a requirement to the IT department to supply a snap shot of data the user then has to wait until this request is fulfilled before they can take the data supplied, extract the exact figures they want and then marry this data to department data to actually get to the insight that they are looking for. Compare this with the near instantaneous results of a search request to any one of the major search suppliers on the web whilst on the internet and you can completely understand the user’s frustration.
The new swath of vendors offering to supply the answer to this problem have realized that the business users have become disappointed by the inflexibility over the last ten years of Corporate BI implementations to provide insight into their corporate data. These new “Self Service” tools being currently offered seem to be the solution to this problem in that they combine interactive visual analytics with data integration and near instant results for even complex BI cases. This means that the new vendors are ensuring that their sales effort is placed firmly with the Business Community in most cases to the detriment of the IT Community.
The major concern that I have with regards to these tools is governance of data or to put it another way “One Version of the Truth”. The need for Business Intelligence Right Now (BIRN) to support critical business decisions based on insight into multiple data sources is well understood by the Business however as they cannot verify the data once it has left the rarified air of the BI Semantic Layer they cannot guarantee it is the one version of the truth. This is also a major problem with most if not all of the current tools on the market supplied by various vendors is that they also cannot guarantee that they have governed data as most either store the data locally or only use a snapshot.
This problem has been identified by Quest Software who currently has in development a number of tools which will aid collaboration between not just IT and the business but also between business departments utilizing the “One Version of the Truth” as the core of their systems. Self-Service BI is not a myth, but with too many supposed “self-service” solutions are being designed (knowingly or not) for a the more technical user who sometimes identify themselves as “Data Analysts” and have far too much complexity for the normal Business Analyst (BA). The BA has no problem with a pivot table in excel and understanding the business relationships of the data but when faced with a requirement to understand SQL or Data Architecture struggles. Taking this into consideration Quest has designed two separate tools one for the Technical user and one for the business user. Both are easy to use, intuitive and have the ability to integrate and analyses data from many disparate sources and then provide visualization and basic dashboard reporting their critical difference however is that they supply a secure connection to the company’s BI infrastructure to provide the governed data required to make the insight provided correct.
Data mashup within Business Intelligence (BI) applications is one of the latest must have requirements that I have been asked to build into solutions that I have created for some major enterprise clients recently. As mentioned in my last blog about the growth of NoSQL use within the BI area I believe that the mashup can be another useful tool to be added to the BI solution – but it must not be utilized to the detriment of the core principles of any BI solution. The first types of mashup used mapping services or photo services and combined these with relational or excel data to create a visualization of the data. In the beginning, most mashups were consumer-based, but recently the mashup has started to interest the wider enterprise. Business mashups can combine existing internal data with external services to create new views on the data.
The problem with the clamour for the most up to date technology to be added to the BI application stack is as always the differing understanding between the business user and the developer to how they can be used. The battle from the developer’s point of view is trying to get the people within businesses to understand what, how and where the mashup can be utilised within their organisations. The problem from the business point of view is trying to emphasize the speed at which this development must be available to the business. Mashups can enable nontechnical users to build dynamic views of disparate data that are personalized, context-rich, role-tailored, and ad hoc to explore this data in greater depth. However the problem with most of the currently available BI Vendors mashup applications or plug ins is that they simply offer a numerical analysis of data via the normal OLAP cube route and then attach a search bar alongside this analysis to enable a search of separate silos of either textual, web or unstructured content to match up with the data already recovered and analysis.
The ability of a mashup to pull content from other sources is what most business users are excited about and this combined with the ability to store non structured data in a NoSQL environment which allows for rapid search and retrieval and storage of any and all linked data. Most corporations are now requesting that BI systems have the ability to interrogate social networking sites to find out what is being said about their products – this is a perfect example of the ability of mashups to provide information that most marketing mangers and sales teams desperately need to understand to improve business productivity and sales success. This requirement to link to all types of data also needs to be paired with the ability to interrogate all systems that are available within the corporate environment – there is no point in having a BI application which has the ability to mashup data if it cannot attach to all the clients information. These results should also be shown not only in their normal context but in a context that is easy to understand and use for the customer.
I see mashups extending the current traditional data-driven BI solutions to incorporate traditional planned data from a normal RDBMS or OLAP cube adding in unstructured data and accessing further information from either RSS or the web utilising web services. Most of the modern BI Solutions can solve the first two connections but to connecting to the web can require either a web service to be hand coded or the purchase of one of the specific connection applications available currently on the web. As reported last week in the Briefing Room with Mark Madsen http://bit.ly/l0C1Cy , Quest Software are about to bring to the market a group of tools aimed at both the Data Analyst and the Business Analyst/User which will allow for the full range of mashup capability to be available on the desktop for both those in IT and those in the Business. This can only help to improve the harmony between these two areas of the business which will in turn allow them to deliver dramatically better business results than when utilising traditional business intelligence (BI) systems.
Business intelligence applications are moving from the traditional connection to an OLAP Data source based on relational database systems to the ability to link to and consume data from a variety of disparate sources including social networks. The ability for a modern BI application to be able to use mashups of data to provide agility when dealing with integrations of multiple types of data sources has led to NoSql being promoted by many as the next big thing within BI. Does this mean that we have seen the end of the SQL style RDBMS system within the BI area – there are many pros and cons for both systems but I believe that there are still a place for both within the BI arena.
NoSQL implementations like Cassandra and Dynamo can scale out past the terabyte and on to the petabyte size by utilizing horizontal scaling and multiple nodes and in particular the costs differences associated between SQL and NoSQL implementations are significant. However each type of NoSQL system uses its own proprietary code for its connections and the system is usually set up for a particular model which enables super fast performance but does hinder the ability to run any adhoc queries on the data.
Companies are now looking to connect to social networking data to enable them to trend sales and customer selections. This data is very unstructured and most is in the form of NoSQL (Twitter, Facebook etc). The problem as I see it for most major business clients is who within their organizations to use to implement a NoSQL BI solution. Most of the requirements of a BI system – large data sets, speedy recovery of data, and display of results to all business users – can be implemented utilizing a NoSQL data set; however the technology does require a different type of technical resource. One possible solution to this problem could be the Toad for Cloud database application by Quest software which I am just starting to look at in more detail – this shows great promise in its ability to interrogate cloud style NoSQL databases like Cassandra, HBase and Azure with SQL terminology and to allow transfers of data between NoSQL databases and SQL databases.
The trade off for NoSQL database is their lack of ACID and their ability to support adhoc querying. Utilizing SQL RDBMS allows us to use standard connections between servers and clients especially those stalwarts of BI Reporting, crystal reports or business objects. It also allows for clean easy connections when utilizing the most popular of object frameworks like dot Net or xml. Normal IT departments normally have at least one SQL data access language expert in their ranks – this allows them to at least understand a BI implementation based on a SQL RDBMS.
In respect of BI my experience has led me to believe that for the majority of EPOS based customers utilizing a RDBMS SQL based application with the possibility of a star based data warehouse will suffice and provide both transactional integrity and the ability to scale as required. There will of course be exceptions to this model including both the requirement to scale out past the Petabyte mark and a requirement for superfast results and it is at this point that I believe the NoSQL solutions can and should be investigated. I believe that both SQL and NoSQL applications will be implemented side by side in many organizations in the future especially as the drive to include social networking data in our results is realized. Many BI specialists including myself already utilize a plethora of specialized tools to deliver results to the customer – I cannot see any reason for not adding NoSQL into the tool box.
Filed under NoSQL, QuestBI
Partook in a live webcast today hosted by Eric Kavanagh and with questions by Mark Madsen. This was the first time I had being involved in this type of forum and I found it to be an energising experience. The meeting was about the Personal Business Intelligence toolset that Quest Software are bringing to the market later this year. The audience proved to be knowledgeable and questions asked were insightful and provided food for thought for all. Mark was very complimentary about our goals within the BI space. Listen to the webcast here http://bit.ly/l0C1Cy in about 48 hours – enjoy.