Everyone is talking about BIG DATA! It sounds so important and exciting that the phrase is now used commonly. From small associations to large businesses, even socially and on Prime Time TV advertising we hear the buzzwords! These are very exciting times for data analysts because on the continuum of data analytics, big data is very advanced in many ways but basic in others. To learn more about the definition of Big Data – see our post: What’s the Big Deal about Big Data for Associations?
For the data analyst, working with Big Data involves the following:
- Business intelligence (BI) and business analytics (BA) involve important processes for analyzing data across all functional areas in order to guide:
- Strategy development
- New opportunity creation
- Business intelligence (BI) involves turning data into information and then using dashboards and scorecards to present.
- Business analytics (BA) creates value and transforms information into knowledge using statistical methods for explanatory and predictive modeling.
- Turning data into information requires:
- Technical infrastructure
- Data collection tools
- Mining and analytical software
- Data visualization
Where’s the data in an association?
- In CRM, AMS, LMS and other software systems
- In spreadsheets
- In the cloud
- On the Internet
- In data warehouses
- Data aggregators and third party vendors
- The project and amount of data available determine the statistical methods used:
- “Big Data” requires a test and learn protocol and this can be expensive. Many different techniques exist depending on the type of data and desired outcome. Often it’s best to start with your “small data” and augment it with big data, such as census or social media data.
- Small data should be collected from association systems and often individual spreadsheets.
- Data should be cleaned and merged at some level before beginning the analytical process.
- Purchased data needs from data aggregators and other third party systems should be integrated into a working data file or data mart.
Associations can be data-guided and not be using big data yet. Many associations are starting with basic aspects of data management, such as cleaning, verifying or reconciling data across the organization.