Big Data

• Big data is data that contains greater variety arriving in increasing volumes and with ever-higher velocity
• Data Volume:

  • As of 2012, about 2.5 exabytes of data are created each day, and that number is doubling every 40 months
  • More data crosses the internet every second today than was stored in the entire internet 20 years ago
• Companies have an opportunity to work with many petabytes of data in a single data set - Walmart collects more than 2.5 petabytes of data every hour from its customer transactions
• Data Velocity:

  • Real-time information makes it possible for a company to be more agile than its competitors
  • Businesses can make decisions that provide strategic competitive advantages if velocity can be handled
• The MIT Media Lab used location data from mobile phones to infer how many people were in Macy’s parking lots on Black Friday making it possible to estimate the retailer’s sales.
• Data Variety:

  • Many of the most important sources of big data are relatively new, like the huge amounts of information from social networks
  • The structured databases that stored most corporate information until recently are ill-suited to storing and processing big data
• The declining computation costs mean previously expensive data-intensive approaches are quickly becoming economical.
• Big data is Prescriptive - the analysis reveals subsequent actions should be taken to achieve goals
• Big data is Predictive - provides likely scenarios of what might happen through the ability to process an almost unlimited range of variables
• Big data is Diagnostic - looks at past performance to determine what happened and why, improving KPIs
• Big data is Descriptive - real-time dashboard reports to analyse what’s happening now
• Big Data Applications:

  • Finance systems use advanced analytics (e.g. probability analysis & competitive trends)
  • Enterprise Resource Planning
  • Health services can generate realistic forecast models to predict the outbreaks of epidemics
  • Customer behaviour on product and content consumption
• Big data is crucial in decision-making and the growth of data size and algorithms poses an issue in understanding cause-and-effect relationships and potentially misinterpreting results.
• Coordinating interfaces in applications for big data can become an issue between divisions.
• IT Security can pose a risk as the integrity of cyberspace is essential for the effective management of a company. Focus on encryption, updating systems, compliance and training is necessary.
• Legal issues over ownership rights and data protection principles can arise with the use of big data. This risks causing legal costs for organisations.
• Big data can assist in analysing financial statements, running complex accounting models and link geographically dispersed organisations.
• There is a risk that big data may take over the development and calculation of accounting information systems and the presentation of information.
• With the use of big data, accountants can focus on developing new metrics, learning analytical skills and creating visual data representation.