Does Big Data mean Big Risks?
There is no doubt about the fact that in an increasingly data-driven economy, the one has the greatest control over data wins the battle – and nothing quite matches the example than Big Data.The phenomenon of Big Data has enormous opportunities for businesses in being able to leverage greater data and insights for their corporate goals. This has the capacity to lead to better business decision-making, in which firms can effectively utilize resource allocation decisions that can lead to minimal waste and maintenance costs.
However, making the most of Big Data isn’t exactly as simple as talking a walk into a park. In fact, it can be more aptly described as journeying across the near infinity size of the universe and not knowing how to get back to planet Earth. In other words, with big data comes big risks, and companies that are eager to capitalize on such developments need to be conscious of such risks so as not to waste their resources and costs.
The risk of collecting bad data
Since big data involves managing very large datasets, there is a huge risk of businesses collect irrelevant and outdated data. This could happen if companies neglect giving importance to data project strategies that will allow them to storing relevant data based on a set of metrics and indicators.
The failure to analyze data quickly will cause a significant amount of data to be out-of-date, causing the organization to fall behind with respect to its competitors.
The tendency to use bad analytics
Another big risk or challenge that organizations can fall into is the ease at which they underestimate the complexity of using analytical tools. Bad analytics is very likely to be a common scenario if data analysts do not account for the intricate webs of data structures, formats, and content. This will make correlating relationships between different factors troublesome, leading to improper conclusion of causal links and confirmation bias.
This potentially has bigger negative effects if the data is applied inappropriate and can lead to ineffective products and services from being launched. It is important that firms utilize the best practices in using their analytics tools wisely.
Big data has big security risks
Owing to the enormous size of big data, companies that adopt it have to come to grips with using a fragmented approach to data, where multiple data centers have to be managed. However, the vastness of big data means that applying encryption solutions cannot be implemented across a numerous data centers, inviting hackers to focus their efforts in conduct cyber criminal activities.
Therefore, the bigger the data, the bigger will be the opportunities for hackers to steal confidential customer, corporate, and employee data, leading to big settlement fees and PR expenses.
Big costs of using big data
Acquiring access to substantial amounts of data also comes with compliance to numerous to data protection laws and privacy considerations, which can erode a large amount of corporate profits. These costs can be mitigated through careful planning at the budgeting stages. However, those who fail at it will have to face the brunt of big costs.
More importantly, big data functions of collecting, analyzing, and interpreting data also involve heavy costs. This is why it is crucial that companies have the tools and resources available to interpret data quickly without losing too much time. This will not only increasing their administrative costs, but also render their entire time and efforts in utilizing Big Data pointless.