The truism, “You learn something new every day” is a common phrase we’ve all heard since childhood. The fact is, the constant pursuit of knowledge can pay dividends both personally and professionally. By educating yourself daily, you are likely to gain new insights, expand your horizons and widen your perspective. Because another well-known axiom is also true: Knowledge is power.
This axiom is equally applicable in business. Organizations that consistently expand their knowledge, broaden their understanding, and increase their analytical insights are stockpiling valuable intelligence and the fuel for innovation and competitive differentiation. It is simple. Knowledge is power and the more power you have, the more likely you are to succeed.
In business, learning something new about your customers, organizational processes and operational efficiencies are a major business advantage. Business users across a range of industries work overtime to leverage their data to uncover market trends and opportunistic business information. However, there are a variety of barriers that prevent even the best organizations from conducting timely analysis to turn data into critical insights.
One key issue businesses face is the management of their enterprise data supply chain. It is often a challenge for organizations to quickly turn raw data into actionable and reliable information. Reliance on traditional extract, transform and load (ETL) tools compounds this problem. Unfortunately, legacy ETL tools are outdated, overly technical and cumbersome. They drain money, time and resources, and leave business users largely dependent on IT experts for any data analysis. Enterprises need modern tools that foster business/IT collaboration, and empower business users to become more involved in data analysis for better strategic analytical insights.
Business users don’t often possess the expertise needed to use ETL tools for data analysis. They must submit these requests to their IT resources, who typically are overworked and overwhelmed with an abundance of similar requests. The request goes to the back of the queue, creating a backlog of tasks. By the time IT addresses the request, the data is outdated and irrelevant for their business purpose.
Transitioning towards modern self-service data and analytics technologies enables enterprises to provide business users greater transparency and flexibility to enable advanced analytics without creating an IT bottleneck. With a comprehensive data intelligence platform, organizations can eliminate time-consuming, manual data prep procedures. They can deliver data to business users in real time – without waiting for limited IT.
With a comprehensive, integrated data intelligence platform, enterprises deliver business users a self-service data experience that combines data governance, data analytics, and data quality to meet their data needs for better business insights. The long wait times of traditional data prep are eliminated, as users can access any data source easily, and simply acquire and parse that data in a fraction of the time. In addition, business users can visually collaborate as they extract, prepare and analyze data from unrelated sources, and create a comprehensive source for analysis.
With transparency into every step of the process, and with the automation of data blending and cleansing to enable users to profile, aggregate, correlate and transform selected data, the power of advanced analytics is now at their fingertips. With a unified toolset for preparing data, creating models, and embedding those predictive analytics within any business process, organizations can uncover analytical insights that were previously impossible to find.
A great example of finding previously undiscoverable analytical insights comes from the telecom industry. A leading satellite radio company was leveraging legacy tools to help track free trials, paid subscriptions, and lapsed subscriptions. When a consumer purchased a new car, they received a 30-day free satellite trial. These legacy tools reconciled those who signed up for a paid subscription and those who didn’t, but the process was labor intensive and required extensive manual intervention. This resulted in rampant issues with paid customers not receiving their service and unpaid customers continuing to receive services after the trial period expired.
By leveraging an agile self-service data solution, the company quickly determined significant errors were costing them both money and opportunity. Their legacy tools were incapable of tracking subscriptions in real-time. Customer experience suffered, as paid users were understandably frustrated when they stopped receiving services, while others continued receiving services without charge. The opportunity for timely follow-up with trial participants was also squandered. By streamlining the program and timely data analysis, the company eliminated waste, saved time and money, and improved customer satisfaction.
Data analysis can have a major impact on an organization’s operational efficiency and overall growth. With a modern approach to data prep and analytics, enterprises can empower business users to gain impactful knowledge into the customer experience, operational effectiveness, and enterprise-wide business processes to grow revenue and develop data-backed solutions. Combined with data quality and data governance for an integrated solution, companies can streamline their overall data management strategy and ensure maximum return on their data.
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