Big Data Doesn’t Always Mean Big
With the growth in technology, big data has become a trend in almost every company. The buzzword big data, which is used to refer to the vast amount of data a company collects, can be heard in every major meeting. People tend to believe that the bigger the data, the better off the business is. This idea is held as truth in almost every business. Now, everybody is rushing to collect as much data as possible.
However, this maxim isn’t always true. Having big data is not a guarantee of better business. What matters the most is collecting the right data. As much as having big data can put your business in a good position, it can also cost you a lot to extract the data. Think about it, imagine you have years worth of data and you want to find specific data to make to help with a specific situation. It’ll take ages for experts go through all that data to find what you need.
That is not to say that big data bad. Every company can benefit more data. The key is to have clear guidelines for you need. This starts from the very first day you start collecting data. The methods you use to collect data also play a role.
Best Practices for Big Data
Many companies focus on gathering as much data as possible. Eventually, the question changes from, “How do we gather more data,” to, “What do we do with this data?” This is what you want to avoid. Because it is not about piling up data but gathering what can help you in the future.
It is easy to collect unhelpful information, which can hurt the company. Since your team of experts have to go through large amounts of data before making meaningful, policy-based decisions, sometimes they might reach bad conclusions which will affect future policy decisions. That is catastrophic for the company. The quality of data you use to make decisions should be high-quality and accurate.
Big data can be used for many purposes. For instance, the data may be used to advise the future of training and development, taste and preference changes, price changes, market approaches, as well as other business operations. Companies need to clearly define what you want from the big data. That means you should know what type of information you want to find in the data.
Find Useful Data
When you clearly define the purpose of your data search, you can then start the collection process. Remember the key is not to collect a vast amount of data but to collect and store useful data. The actual amount you collect isn’t technically important.
Instead of collecting all company data seek out only that which is useful. This simplifies your job when it comes to gathering information.
Allow every department in your company to collect its own data. The manager in every department knows what information can be useful to them. So, let them collect their own data for that specific department. For example, let HR collect the data for training and development purposes in the future. This process can be automated in the IT department. You can have systems made specifically to collect some data as you go about your daily routines.
Automating this process ensures that the data is collected within a boundary and specific guidelines. The automated process cannot miss any data that is supposed to be stored. It also makes sure that the data collected is correct as the system can flag any errors.
The Bottom Line
The term big data has misled many people to believe that it is important to collect every data point available. Don’t make this mistake. Tiny errors that occur when collecting data translate into bad information gathered from that data. After collecting bad information from your big data, your company can be in danger.
This is why you should be careful when collecting and mining data. Get people with experience to do this job since a simple error could lead to catastrophic decisions for your business.
The key is having good accurate data. It can be big or small depending on what type of business you run. Subsequently, never compete to have the biggest data sets as that may only add more problems to your business. Data mining can be expensive when the data overly comprehensive.
As the saying goes, garbage in, garbage out. All data sets are meant to help clarify the state of the industry in general and the business specifically. Unnecessary data collection will only lead to more noise and confusion as you try to parse out what the company’s next step should be.
Hopefully now, with this important concept in mind, you will revisit your current data collection methods and see if their measuring anything meaningful to the company, or if your data collection is just adding to the noise.
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