Centralizing the Financial Data Story

Centralizing the Financial Data Story

Data was supposed to solve everything. Once professionals figured out how to mine the data being generated by customers and business operations, the insights gained were supposed to instantly solve problems and streamline processes. And while data has greatly contributed to these types of transformations, it has also muddled the role of the CFO. A new survey conducted by CFO Research revealed that many CFOs still struggle with managing the data of financial planning and analysis intended to help their companies. In a nearly even split, CFOs either complain about not having enough data (32%) or having too much (30%). This disparity shows how the value of data mining on the financial side of an organization has varied depending on the systems, the CFO, and the intent of analysis. Regarding the future of data analysis, almost all CFOs (94%) agree that up-to-date and instant data is the only way forward. With this expectation creating more corporate pressure for actionable insights, CFOs need to find a way to collect the data they need, whether it’s more or less, and how to write a cohesive story with the results. Knowing Where to Look The biggest areas where CFOs are and should be using analytics include assessing customer risk and behavior, compliance and regulation, and evaluating the fluidity of their future operations. Many CFOs struggle with analytics, because they are using them to address all these different areas with a single set of data. The solution to centralizing how data is used is to apply only the appropriate data to the corresponding areas. Using customer behavior data to address compliance concerns would...
How Big Data Can Shorten Your Commute

How Big Data Can Shorten Your Commute

When people think Big Data, they usually think about how it is used by businesses to gain better insight into the needs of their customers. Often not considered is the many ways they can benefit from its use in different facets of their day-to-day life, including in entertainment, security, and healthcare. For example, one area where Big Data proves to be very useful is in transportation: Nobody likes sitting in traffic. Not only does it waste time, but it also has a negative environmental impact and inherent health risks, such as weight gain, high blood pressure, and increased stress levels. Recent advances in the use of Big Data in traffic management, though, have helped measure traffic patterns and trends all over the world so that drivers can be more equipped to make decisions that speed up their commute. Saving time, saving lives One way in which Big Data can alleviate traffic is by speeding up response time to emergency situations. Cameras and sensors on the road can notify dispatchers of accidents sooner than people calling 911 can, and as such, assistance can be more promptly provided. Not only will this clear up traffic quicker, but anyone who may have been injured can receive crucial medical attention faster. Apps like Waze also use Big Data to help drivers plan or adjust their commute. Information about road conditions is constantly updated and crowdsourced by users so that drivers can be made aware of where traffic is on their route, what’s causing it, and alternative routes they can take to avoid it. Other apps also help people save time on the road....
The Benefits of Utilizing Unstructured Data

The Benefits of Utilizing Unstructured Data

Data that has been qualified and enters a system with some definition and parameters — AKA structured data — is an easy way to begin a data journey. However, to really get the most bang for the buck when it comes to data, enterprises should also be using its unstructured cousin. Unstructured data is less understood by companies than structured, but make no mistake: It is as vitally important and useful. In fact, a recent Aberdeen Group report found that businesses using unstructured data are twice as likely to be satisfied with their data quality and usability. For those who use unstructured data frequently, 60% are happy with the ability to share data and 50% are pleased with the accessibility, compared to 18% and 20%, respectively, of companies who rarely use unstructured data. Understanding unstructured Experts estimate that 80% of all data is unstructured, too, meaning that companies not taking advantage of it are missing out on a huge chunk of useful information. While structured data is made up of clearly defined records or created with an existing data model, unstructured data is everything else: It is usually text-driven and comes from digital sources without predefined formats. The following examples are the most commonly mined sources of unstructured data: Social media. When a customer mentions a company or product on social media through a post or comment, that instantly becomes unstructured data that can be mined for important insights. Internal collateral. Data can also come from internal sources including videos, presentations, marketing and sales collateral, reports, and even the casual email thread. Customer-generated content. Social media aside, this comes in the form of online...
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