Every business today knows the importance of Big Data and how it can be used to reach better judgments. Unfortunately, some businesses end up assuming that it is enough to collect massive quantities of data, but that is not enough. Tech companies will often discuss the three or four V’s which make up big data, with IBM listing volume, veracity, velocity, and variety.
All of those four V’s are important, but it is the last V in particular which companies need to think about more. We value diversity in the workplace because people from different backgrounds can think of different solutions and perspective to a problem, and the same is true with data. By improving data diversity and looking to collect data from a wider variety of sources, your analytics workload will improve.
Structured and Unstructured Data
Despite all the talk about Big Data, plenty of leaders and businesses do not really understand what it is. You think of those times when you collect data on a spreadsheet or database, and thus assume that Big Data is just a bigger spreadsheet.
That is not the case, especially when we consider that Big Data consists of unstructured and structured data. As Bright Planet states, structured data is highly organized and can be easily searchable, while unstructured data is not. The numbers on a spreadsheet are structured data, while photos on a Facebook account are unstructured data.
If you want to figure out how to improve data diversity for your mobile car wash and detailing service, you have to look at unstructured data. Unstructured data may not fit easily in a spreadsheet, but it can offer better information than structured data because humans communicate with pictures and words more than numbers. Businesses do not have to search for additional data sources as they possess unstructured data in their own texts and documents. By integrating qualitative, unstructured data and putting it into a data lake, businesses can create a more diverse and superior data source.
Establishing Trust
Gathering data from a wider variety of sources sounds good, but casting a wider net means that you are more likely to retrieve flotsam. Improving data variety means making greater efforts to improve data veracity at the same time.
There are many steps which can improve data accuracy, but there are two important things to note. First, if different business departments control different information, then no one has a complete picture of the data. Avoid self-contained data silos and use a data management platform which can integrate all data into a single platform.
Furthermore, make sure that your data is constantly up to date and cleaned. Use a data scrubbing software like the ones listed here to remove incomplete and poorly formatted data. Even formatting mistakes such as whether to use Month/Day/Year or Day/Month/Year can add up and ruin a data lake, and so your business should discuss how to keep formatting consistent for everyone.
Improve Data Literacy
In order to get the most out of big data, companies have to grant access to not just IT, but a wide variety of users so that they can use the data lake in their own way. But just as it is important to ensure that your data is accurate, you must ensure that your users know how to use data in a constructive manner.
This means several steps. First, you have to get employees to feel comfortable using data instead of their gut. Ask for employees to use data when giving presentations or taking surveys, and also use it yourself to set an example.
Second, you must help employees develop the critical thinking skills necessary to analyze Big Data. Set up regular training classes talking about the dangers of confirmation bias, the importance of using an appropriately sized data set to draw conclusions, and understanding that correlation is not causation among other logical flaws.
It should be noted that even with the appropriate training, employees will make mistakes with data and you may be tempted to only let a small number of IT professionals and management have access to Big Data. But improving data diversity and employee data literacy go hand in hand, as you need a larger number of people to analyze more diverse data sets.
Data for Everyone
Despite the name, Big Data is not about collecting as much data as possible. It is about ensuring that you have an accurate, varied data set which will help your business’s analytical process. That means collecting data from a wide number of quantitative and qualitative sources, and giving everyone in your business access to said data.