Jason Jameson, Director, Analytics, IBM ASEAN
Business Intelligence (BI) is one of the universal topics of discussion from behind closed doors of executive suites, across Lines of Business and within the data centre. In this first in a new series titled “Briefly Talking Business Intelligence” Data & Storage Asean editors approached technology leaders to take their view, their pulse of the BI marketplace and how it is impacting local and regional businesses as they drive forward big data initiatives.
We begin with Jason Jameson, Director, Analytics for IBM ASEAN.
DSA – What’s the difference between Business Intelligence tools and Big Data Analytics tools?
Jason Jameson: Business Intelligence (BI) is a subset of Big Data Analytics (BDA). Traditional BI tools allow you to scrutinize data based on your own hypothesis. The data needs to be standardized in specific format before it can be analyzed. Perhaps the simplest form of BI is the spreadsheet. For example, you can create formulas to produce outcomes from a spreadsheet that has been fed a set of numbers.
With BDA, you can crunch structured and unstructured data in whatever format that the data is made available. And based on that, the BDA tool can generate a list of queries or questions for the user to choose from and decide what it wants to get out from the data. BDA helps you discover insights that may not have been possible previously.
The key difference is the output from BDA is comprehensive and incisive. BI gives you a dashboard view without the depth that can help make business decisions.
In summary, BI tools allow us to answer questions that we know i.e. "what are our KPIs from a data warehouse?", while BDA allows us to answer questions that we do not know previously that we should be asking.
DSA –Should BI be put in the hands of ALL staff?
Jason Jameson: The question should be if we want our team to make better decisions. If the answer from the management team is a resounding yes, then the workforce needs to be trained on how to use the BI tools to differentiate the types of data and how data should be processed to produce desired results. But as stated previously, BI is a subset of BDA and in order for a team to get the most out of data, comprehensive solutions that process structured and unstructured data is needed.
This has implications for skills and training, as Big Data tools evolve they are becoming far more accessible to the average user. This means there is an opportunity to train staff to explore and discover data in Big Data - what data scientists primarily do today - in the same way that we have trained staff to use traditional BI tools, spreadsheets etc.
DSA –What Can a BI product achieve that a spreadsheet cannot?
Jason Jameson: BI products can be customized to crunch massive amounts of data to provide useful information. With BI, you can draw correlations between different data sets, or between structured and unstructured data. For instance, you can analyze weather data from a myriad of sources including real-time data from IoT devices. And it can be done very quickly. A spreadsheet will not have the same speed as a BI product in handling large volumes of data, but spreadsheets are still a useful tool for presentation and manipulation of results from a BI tool.
DSA –What are the key considerations when choosing a BI product
Jason Jameson: The key considerations are easy to use, high performance and sufficient functionality to cater to the user’s growing sophistication plus the same experience on desktop browser as well as mobile. You can tell that a user is becoming sophisticated from the type of queries that arise. IBM Cognos and SPSS are two examples of applications that give an extremely rich toolset for users to start small and scale as their needs and requirements grow.
DSA –What’s Unique about your BI offering?
Jason Jameson: The beauty about IBM is its broad and richly diverse range of product offerings that can cater to the casual user to the data scientist. Granted we did acquire many of the solutions but the great part is our ability to integrate the solutions for enterprise use. For example, a casual user can use Watson Analytics as it is available online. More than 6,000 users from Asia Pacific have registered to use Watson Analytics. An enterprise or a business can opt to use either IBM Cognos or SPSS depending on their needs. A Malaysian telco, Celcom used IBM Unica to create targeted marketing campaigns.