Big data brings a new wave of opportunities for companies of all sizes and types. It is the harbinger of a new era of understanding about organizations, their nuances, their opportunities and their challenges. But it is also a highly complex and, in some cases, confusing field for many due to its many layers.
The digital world has given rise to an abundance of data. We have an abundance of information at our fingertips, more than ever before. But what can we do with all this valuable data?
1. Believing You Need to Use All the Data
Companies collect enormous amounts of raw data every day. But with so much information at their disposal, it can be difficult to determine what data is valuable to them. It is important for companies to separate quality data that can help them make informed decisions from that that is not useful and can even hinder their efforts.
Furthermore, data must be cleaned and explored to gain insights that the company can actually use. Often information in its rawest form is not that useful. Remember that there is bad data, which can negatively impact your organization.
2. Not appointing a data controller or team
Data science is a niche market for a reason – not everyone is an expert at it. Rather than assuming that your current team can handle data analysis, it makes more sense to appoint a specific data person or team. Employ people with data science experience and knowledge to collect, clean, mine, manipulate, and make informed decisions about how best to use it.
This executive or team will serve as a go-to source for big data, helping your company understand how data will better inform and support its efforts.
3. Not having an adequate data management system
In addition to having a person responsible for big data in your organization, there must also be a system for managing, storing and using the information you collect. Work with your team or chief data officer to establish a logical structure for handling the data the company generates to ensure it is managed and used correctly and efficiently.
Consider customer relationship management (CRM) software. This is the type of organizational tool that allows you to organize information about clients and customers to better use it effectively.
4. Stop trusting the cloud
Even in the digital age, some companies still rely on outdated storage solutions to collect and maintain their information. These are not only less efficient than newer alternatives, but also less safe.
Cloud solutions are ideal for storing and managing data, as well as ensuring adequate accessibility for anyone who needs it. Cloud-based solutions are also significantly more secure than individual servers. Plus, they can scale with your business, growing with your company as needed. From SaaS tools to file storage systems, cloud-based solutions are all about maintaining and generating more information for your business.
5. Investing in fancy, expensive tools you don't need
Some organizations always want to be at the forefront of technology, so much so that they invest in expensive tools that are not really useful to them. This certainly applies to big data tools. For example, a company that doesn't actually generate large amounts of data may want to readily pay for data warehouse technology when it doesn't need it. After all, warehouses won't solve many problems or store certain materials.
Instead of looking for the next big tool, consider what your business really needs. It may not be sophisticated and expensive equipment.
6. Ignoring security
Security risks are inherent to any technology. Because big data and technology are intertwined, it's important to pay close attention to the risk of data breaches and other threats. These measures may include:
- Grant access only to those who legitimately need to use the data
- Implementing multi-factor authentication systems
- Using the cloud storage systems mentioned above
Business leaders must be aware that data can be widely accessible to people in many different locations and that no system can keep it 100% secure. For this reason, they must also implement measures to address and minimize violations if they occur.
7. Thinking about the small picture rather than the big picture
It's called big data for a reason. While it's obviously important to focus on the details and use data to inform your small-scale initiatives, it's also a good idea to think about the bigger picture. Ensure every decision you make is supported by data, including your long-term goals and objectives. This may include scaling your organization, developing company-wide strategies, and so on.
If you ignore the big picture and get caught up in smaller pieces, you could be missing out on what's real. opportunities .
8. Following trends instead of common sense
There is a lot of excitement around big data. But the trends you see in the media aren't always the best strategies for your business. Instead of trying to align your methods with the latest trends, work with your data analytics team to determine the best path forward for your specific organization. While you, of course, shouldn't resort to outdated strategies, you shouldn't necessarily adopt a trend just because it's in the headlines.
9. Not using your data enough
Data shouldn't just sit there – it should be used. The vast majority – if not all – of the decisions you make should be supported by the data you collect. So don't just let it sit in one repository. Act accordingly to get real, measurable results. It has the power to completely revolutionize your business.
10. Relying too much on data
At the same time, not all data has all the answers. It is essential to recognize the limitations of big data and know when to use it — and also when not to use it. Also, keep in mind that data may indicate correlations without proving causality, and sometimes it may be necessary to gather more information before making decisions.
