28 Sep Applications of Data Analytic Tools
Data is being created, stored, and used for analytics even when you are not thinking about it. Organizations that have adopted data analytics or are in the process of doing so are quick to realize its limitless business potential.
The purpose of owning tools for data analytics is so that you can use these tools to take advantage of business insights. By using the right tools, businesses can hope to gain insights by looking at their aggregated data and analyzing it to form new business objectives or optimizing current ones.
Here are some use cases on how using the right tools can reap your business the correct benefits from data analytics:
Customer Relationship Management (CRM)
Creation of dashboards that meshes and analyzes data to present it to customer service, sales, and marketing management in a way that is digestible and insightful to decision-making and strategizing.
Such dashboards could include information on demographics, household income, policies, and generic data such as customer name, age, addresses, and things of the like. This information and the accessibility to it through a tool such as dashboard analytics would bolster the toolkit of any company’s CRM strategy.
Financial, business, and data analysts all could improve their work by using data analytic tools to streamline operations and maximize profits. Dependent on the tool, data could be drawn from various multiple sources with frequent updates to provide weekly or monthly reports.
Furthermore, data-driven reports could highlight business problems which would then enable management to take corrective action.
Data reports are a great way to use analytics to gain insights but another tool manifests itself in the form of smart recommendations or suggestions. Depending on how advanced your toolkit is, there can be incorporation of Machine Learning (ML) to have your system suggest changes or improvements for business processes. This automated and analytical response by the system, driven by data, will improve business decision-making and cut down time-to-market.
Applying the correct data mining tools can highlight problem areas for architects and engineers. Daily tasks that are logged can be reviewed by users of varying roles to identify anomalies or inconsistencies. With enough data, graphical representations can be created to predict launch dates, expected down times, asset dependencies, and other variables.
When the subject of data arises, no one can relate more than researchers and analysts. Despite whichever industry you are in, successful businesses are likely to be staffed with quality analysts that fuels their businesses with data insights. With the amount of data increasing by the year, the workload for these analysts would only naturally get heavier. Using tools and software that help these workers digest data in a timely manor would benefit companies in the long run.