At DFX5, we ask our clients to define how they measure success. The results are so informative, that we have compiled a list and share with new hires to teach how companies, teams, and even a same individual measures success in different ways. A strong school of thought believes increased bottom lines and decreased expenditures drive success, while others consider community impact and quality of life as the true key metrics. Regardless of how you measure success, the results always include a look at previous and current market conditions and the performance exhibited within those markets. Therefore, to truly measure your unique definition of success, we must start by developing a process to capture performance, anticipate market conditions, estimate potential outcomes, and the validate the accuracy of the predictions, to then impact subsequent actions. The process will measure any definition of success and will provide an iterative loop of improvement.

DFX5 measures success using real-time cloud-based tools that can handled billions of messages per second. For a financial firm we implemented a ticker tracker that was monitoring the fluctuations in prices for various commodities and would take proactive actions when certain scenarios were detected. The real-time information can handle any type of messages and can communicate with other systems for ad-hoc analysis and reporting.

DFX5 develops the world’s most advanced databases using modern tools including NoSQL and graph database technologies. The event driven database can handle many events with disparate schemas and with diverse consumers, within a highly secure, robust, and scalable system that can provide answers with micro-second latency. The result is that your data will not be limited by technologies or schemas, instead a proper data governance structure to handle all data can be developed in full compliance of company and business rules for access and security controls.

Ad-hoc analysis tools including engines like Amazon Athena and warehousing tools like Amazon Redshift are part of the toolkit of services used to track and measure success. The analytics tools allow your data analysts to perform queries to answer key questions and find business insights. The analysis and queries are then fed into machine learning models to teach the artificial intelligence tools to identify the same patterns and business insights your data analysis teams are already using to drive decisions. We train the machine learning models to learn from what your team does, and then go out and find similar insights on its own. Therefore, expanding your capabilities and services.

Our proven models have provided machine learning advantages for multiple organizations. Since all information is tracked and stored, systems to analyze the data using machine learning and advanced mathematical equations are easily integrated into the solution. The result is a system that uses machine learning to find hidden patterns in your data, correlations between parameters, and proactive actions to increase your definition of success. The baseline models work for any industry, sector-agnostic, yet are configurable to adjust the model to fit your measure of success. The model becomes an extension of your organization. Once this is achieved, then we begin adding new attributes that are currently outside of your measure test, and we iteratively train the model to become smarter at measuring what you define as success.

AI/ML performance tracking tools are a game-changer, we unleash the power of AI/ML to look back and determine the performance of your investments with comparable scenarios. For example, our tools can crawl through large money markets financial data to identify fraudulent transactions or portfolio management analysis.