Which of the following statements about big data is actually not true? You are probably asking yourself this question, if you’re part of the dialogue that’s currently taking place regarding its future. Part of this dialogue involves folks arguing about whether or not a business can really utilize big data and its myriad of new capabilities to make decisions that will ultimately improve its bottom line. Another part of this conversation involves folks arguing about whether or not big data is truly the wave of the future. Finally, some folks are concerned that using big data for decision making is not a wise move for companies, businesses, governments, etc.
Folks are often concerned that big data and its various capabilities aren’t feasible because of one reason or another. But the truth is that these types of concerns are baseless. In fact, today’s technologies, specifically those that reside in the cloud, are very mature and provide businesses with many capabilities that were impossible a few short years ago. Just consider what’s available in enterprise-grade data visualization tools, for example. You can now easily visualize and analyze information from all sorts of sources in order to detect trends and patterns and to make inferences about previously unknown or even unknown variables or trends.
Yes, it’s certainly true that the world of big data has made a lot of people very rich. It’s also true that lots of people have been negatively impacted by the use of big data and the misuse thereof. But that shouldn’t stop folks from trying to use big data. After all, businesses need to utilize big data to identify new opportunities, recognize emerging threats, and pursue new market segments. And without misuse, big data can be a powerful tool.
However, misuse can certainly occur. There are certainly many cases when companies have used big data improperly and have faced a variety of problems, including legal ones. In addition, big data itself is not infallible. There are times when it does not apply, when it leads to wrong conclusions, when it fails to yield useful insights, or when it doesn’t provide the necessary data in order for business managers and executives to make informed decisions. All of these issues highlight the need for you to ask yourself which of the following statements about big data is true?
Yes, it’s true that sometimes it’s not always right. Data scientists and computer programmers working at Facebook were caught by surprise by one such example: they tried to use data analysis tools to predict different types of behavior based on user demographics and interests. Their predictive algorithm plugged into the company’s data structures, and it turned out to be basically what the Defense Department was looking for! Of course, this particular case illustrates the dangers of relying too heavily on aggregate data. So, yes, it’s definitely true that sometimes big data is not a good tool.
Yes, it’s true that sometimes it is necessary to go with a more expert opinion. When we say “go with” this kind of expert opinion, it means hiring a team of scientists, programmers, computer experts, marketing experts, and business mentors to focus on improving the accuracy of big data tools and algorithms. In the end, though, this can cost businesses hundreds of thousands of dollars in hiring and training professionals. In the end, though, this can actually save businesses thousands of dollars in avoiding costly mistakes, as well as in identifying and solving real problems. Again, though, this type of expert input is often required in order for companies to make the most of big data tools and algorithms.
Yes, it’s true that sometimes it is necessary to go with the expert opinion, despite the fact that it may cost companies thousands of dollars in hiring and training experts. However, many business owners are already suffering through this problem because they have failed to perform due diligence when it comes to data and information that could help them predict market behavior. Indeed, many are still operating in the dark regarding how their competitors and other businesses are utilizing big data tools and models, as well as why they may be having issues with performance and profitability. Of course, if you really want to avoid being caught off guard, you should try to gather as much relevant information as possible. Aside from gathering information, you should also perform the actual testing to ensure that your software model or tool is robust and accurate. Otherwise, you may end up spending even more money on hiring more experts and contractors in order to perform quality testing.
Yes, it’s true that sometimes it is necessary to go with the expert’s advice. However, this advice should be accompanied by hard work, too. Businesses need to invest a lot of effort and time into collecting accurate and up-to-date data sets from various sources. In doing so, they will be able to use big data tools and models to make better decisions. Indeed, using big data analytics can help businesses achieve its goals in terms of increasing profits, minimizing market risks, improving productivity, and maximizing return on investments.