Information storage and management has seen a revolution in the past decade. The amount of information able to be stored and managed has increased exponentially as has our ability to analyze and share it. Today we talk about the application of data for the advancement of business and about how data can help us improve protocols and procedures through the implementation of best practices. Our relationship to data has changed considerably; people are now more aware of their reliance on relevant, accurate data and there is a push towards widespread data collection and analysis.
The term often used to encompass this new body of traditional and digital data (and the methods of its collection) is big data. Why big? Because the largest information collections can only be measured in terabytes – in the trillions of bytes. Certainly not all databases are going to be this large but the tools required to manage the largest databases are going to become increasingly relevant to more and more businesses.
Internet-based analytics and data collection
The way that most businesses will come into contact with big data is through online analytics and data collection. Tracking, counting, and measuring the activities of millions of Internet users at once has given rise to a brand new kind of online advertising. Many Internet businesses concerned with advertising make use of these new analytical tools.
It is not necessary to be an online mega-business in order to take advantage of similar data collection practices. Many Internet-based business intelligence tools are geared to helping small – medium businesses collect information that is relevant and useful to them. Many of these are free or inexpensive to download.
Data that matter to you
Collections of data, regardless of size, are going to be meaningless and difficult to talk about unless you can talk about it in specific terms. Any discussion about data within business intelligence is likely to include some particular terminology. Though any list of current BI jargon is likely to be out of date before very long, these are a few terms that you should be familiar with:
- Velocity: The rate at which data is generated and/or collected. How sophisticated a data management program is depends on the manner in which is handles the constant stream of data coming in.
- Volume: Storing data is not the problem it used to be and there are an increasing number of storage solutions available. Today volume concerns the amount of information passed between machines, sensors, or other data collection points.
- Variety: Data may be structured, unstructured, or multistructured. Structured data exists within a fixed field and is related to all data found within that same field; spreadsheets are a classic example of structured data. Unstructured data follows no particular pattern and is difficult for traditional data management models to handle; text-based information is arguably the primary form of unstructured data. Multistructured data is generated by people interacting with machines; an online search engine query is a simple example of multistructured data. In the future we are likely to see an even greater variety of data.
- Variability: The velocity, volume, and variety of data changes over time. Any data management model must take these changes into consideration and be able adapt to them. If variability is not accounted for then a model will quickly fail.
Knowing about different data types is important because any collection of data is rarely of one type only. Variety within any data collection is going to be one of the biggest challenges of the next several years, especially where Internet data is concerned. Every business owner needs to be familiar with the basics of BI and data. Though our ability to store and look at all the information gathered is no doubt going to keep pace with our needs, our ability to sort and manage it will be continually challenged.
Infographic image: Infographic: The Four V’s of Big Data | The Big Data Hub