Why is it Time for you to Optimize your Financial Analytics?
Let’s be honest: prices are rising, inflation isn’t coming down fast enough, consumers are changing behaviors, and fears of a recession remain. These factors, among many others, increase the need for financial leaders to make real-time data decisions. To do this, they need to be confident in the tools to analyze that data, particularly during financial uncertainty.
Why is optimizing so essential for business intelligence?
Today, Garner estimates the yearly cost of poor-quality data to be $12.9 million, which is a number that should be jumping off the page for you right now. Optimizing your financial company or team's business intelligence can help increase the bottom line while improving your employee's efficiency. For example, suppose your company has licenses to a BI tool with low adoption and is only being utilized by a small portion of employees with access to that license. This would merit some investigation into why the adoption is so low. A well-put-together strategy involving BI starts with ingesting the data into the cloud data warehouse and moving it to a consumable format for executives. These executives may want to check the business's health, whereas managers may want to use the data to make strategic decisions like which company to invest more capital in or which clients are beginning to show more risk than the company is ready to take on.
The key to ensuring that you have the right BI tool is understanding how each user in your financial organization interacts with data and how they use it to make decisions. Based on this understanding, you can then begin to map out the best BI tool and how it can be used by every user so that the data in front of them can drive your company's success and decisions.
How does Sigma fit in?
If you’ve made it this far down the page, you’re probably thinking, “I’ve heard something like this before, but how is this company going to help me?”, well you’re in the right place. While most people think of data as being for engineers or analysts (technical folks), we believe that data can and should be used by less technical users (business users). Sigma is purposefully built for the Cloud Data Warehouse (CDW). It enables your data team to build workbooks and explore billions of rows of live data without ever having to move data from the warehouse. Sigma also helps your company or financial team increase the speed at which they can get insights to make decisions by closing the current feedback loop. That feedback loop right now looks like a finance analyst creating a report for risk analytics, sending it to the business user, and then waiting to see if the business user has everything they need in the risk analytics report. If they don’t, they have to send it back to the financial analyst and wait for the updated report to be sent back. This process can add days or weeks to decisions made, which may be made using outdated data when it is all said and done. Sigma closes this loop by allowing the business user to explore and analyze the live data themselves so that the financial analyst can be freed up to do other things with their time instead of creating ad hoc reports. Sigma helps your team do their job more efficiently, with as little friction as possible.
Cowen Customer Story
Cowen Inc. is a diversified financial services firm that operates through two business segments: a broker-dealer and an investment management division. With as many as 11 million trades running through their pipes daily, Cowen Inc. must continuously process and analyze enormous volumes of data. And as a publicly traded financial institution, Cowen must be able to store and retrieve data about each transaction to meet regulatory requirements and remain in compliance. The company’s broker-dealer division offers investment banking services, equity and credit research, sales and trading, prime brokerage, global clearing, and commission management services. When Cowen first became a Sigma customer, every data request from a business user had to go through the IT department, which then provided the data in Excel worksheets. But Excel’s scale limitations prevented the data from being delivered in a single, comprehensive spreadsheet. The only solution was to break it up into multiple Excel worksheets, which slowed down the analysis process, made it difficult to get a holistic view of the data, increased the possibility of copy/paste or formula errors, and made responding to regulatory requests extremely labor intensive. Cowen has used Sigma to increase finance report creation by 6x the speed, achieve zero ad hoc requests from analysts, and analyze 5 billion row datasets without extracts.
