The business data management market will grow by 14% throughout 2020.
As modern technology continues to advance, businesses become more and more reliant on the use of data about daily operations and their customers. The sticking point for most businesses is that they lack the understanding or means to properly utilize the data.
Big data is a complex beast and it’s easy for businesses to make mistakes surrounding it. Unfortunately, many of these mistakes can be massive and have the power to ruin the profits or reputation of a business.
This article will cover five major business data management mistakes and what you can do to avoid them.
1. Lax Data Security
There will always be security risks when working with big data. Common cyber threats include an outside party hacking into the system or a disgruntled former employee deleting important files.
That’s why it is vital you keep tight control over privileged users and regularly audit edits made to data. There are resources out there that offer automated user provisioning that can help prevent inappropriate access to your big data.
2. Analysis Paralysis
Many companies take the dive into big data without having a proper framework already set up. This can then lead to projects stalling. It’s also common for companies to over-analyze data they’ve collected, which still causes paralysis in the continued collection and utilization of the information.
To help prevent this from occurring, have a well-defined initiative already in place. Data should either support a hypothesis or refute it.
3. Lack of Central Leadership
When you’re collecting massive amounts of data, quality and accuracy will always be a primary concern. The mistake that many companies make is failing to have any central oversight on the collection of data. This leads to duplication of content and erroneous input.
Make sure to have either a person or committee responsible for data hygiene. They can delete unnecessary data and ensure the quality of information is accurate.
4. Letting Data Stagnate
Many companies are collecting and managing data off-site, but failing to extract and implement insights. Instead of collecting as much data as possible and then forgetting about it, designate a team in charge of studying it and finding ways to use it to improve operations.
5. Not Automating Data Energy Solutions
Using data to help improve energy management and improve operational efficiency is key for a large company that might have a massive utility footprint. By making use of an automated system that can collect, analyze, and report energy data, a business can better manage its objectives and cust costs on its data management budget.
Be Responsible With Business Data Management
It is imperative that a company devote time and resources to its business data management. Failing to have a proper handle on the collection and utilization of big data can lead to disastrous results. This can lead a business to have security issues or to stagnate in improving its daily operations and falling behind the competition.
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