Picture:  In an era of high data volumes, it is more important than ever to manage the critical steps in data collection, collation and analysis so that your data is easy-to-use, flexible to grow with your business, meaningful and insightful. 

Managing information in an era of data explosion

Part 2 of 4

In the last related blog article, The Explosion of Gaming Data, we talked about the explosion of data volume that has evolved from the 90s decade of transactional data through to the 2010s with the burst of social and market data.  The growth rate of data volume is increasing at an extraordinary rate – at the moment, it is estimated that the total amount of data points is similar to the total number of stars in the universe.   Organisations are now planning for PBs - not Megabytes, not Terabytes, but Petabytes of data.

With the installation of loyalty programmes that capture play time, expenditure, win/loss, participation in promotions, game preferences and other behavioural attributes of a customer, the sheer volume of data and the complexity of the output is considerable, particularly as we move away from reliance on gaming.   Now, more than ever, efficient management of the entire system is critical.  Look to the future with downloadable games, and you have data volumes that are at least 480 times more than current machines where data is typically stored hourly. (1)

In the first instance, the major decision for organisations is to think about how they are going to store their information.  At the moment, many systems do not store large volumes of information over time - it is quite common for a tracking system to only store up to one month of data at a time.  This makes it very difficult to analyse trends over time, look for patterns or associations in data and make decisions that will increase customer satisfaction and customer loyalty.

The role of the data-warehouse

The first critical step in storing large amounts of data is to implement a data warehouse, a large central database that collects data from one of more sources within an organisation.  This centralisation of data storage enables a platform for organisations to gain an information advantage through the process of transforming data into business intelligence and sharing data with each other.

The main 3 functions of the data warehouse are to stage, integrate and produce data that is accessible for the end-user.  The preliminary step (which is often now thought of as part of the data warehouse) is to collect, clean and validate data.  This is an important precursor for consistently reliable analysis.

Turning data into meaningful information

The data-warehouse becomes the framework for the right analytical tools to be applied, ‘right’ in the sense that they are useful, ones that fit the organisation’s business value proposition.  As the business grows and staff change and technology is updated, the data-warehouse enables a more flexible environment for organisations to embrace new business models and remodel their analytical techniques.

Having access to powerful analytical models that embrace a whole-business approach takes away the exhaustive analysis paralysis that can occur with spread-sheeting high volumes of information that come from multiple systems.  Not only is the information often one-dimensional, but it presents a problem for the analyst in that they find themselves spending large amounts of time collating and formatting information and less time analysing.  The analysis also becomes quite timely, inefficient and sometimes inaccurate because it is difficult to find associations or patterns in the data and apply clustering techniques that help you to define the relative importance of your groupings.  For example, how do you determine the differences between customers that spend in your Bistro compared with those that spend in your Gaming area.  What if they do both, how are they then different?

The underlying principles behind effective information management are data quality, fast retrieval, and actionable analytical techniques that align with your business values.

In our next Part 3, we will look more closely at these analytical techniques. 

(1) The Petabyte Era of Gaming Data, by Dr Ashok Singh and Andrew Cardno, Casino Enterprise Management