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How Digital Transformation Accelerates Finance Analytics
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How Digital Transformation Accelerates Finance Analytics

How Digital Transformation Accelerates Finance Analytics

Integrating digital technologies into every area of your business can vastly improve your finance analytics.

By Armanii Glaspie, September 2, 2021

To stay competitive, modern organizations need to do more than capture all of the data at their disposal — they need to turn that data into insights that will improve operations, business processes and strategic decision-making generally. That requires integrating digital technology into all areas of the business, a process known as “digital transformation.” Companies across the globe are embracing digital transformation because it increases the value they can deliver to customers.

Recent trends, including remote work and increased online interaction during the pandemic, have shifted consumer expectations and increased the value of digital transformation initiatives. Global demand for online banking options, better customer service online and more digital payment options continues to rise.

Because digital transformation eliminates the physical constraints on consumer transactions, it can rapidly increase transaction volume and profitability. Making a payment or diversifying a portfolio becomes almost effortless. Digital transformation can also improve employee productivity by simplifying and accelerating the exchange of information, often via instant access to data stored in the cloud.

Given its clear advantages, there’s no reason to think digital transformation will level off or slow down in the near or medium term. Even as we hope to move beyond the current pandemic, the experiences that it enables will likely become our new normal.

Digital Transformation Enables Advanced Finance Analytics

Finance analytics encompasses a lot of surface area — forecasting, budget reviews and competitive analysis, to name a few — and each discipline can be digitally optimized to improve the way financial data is collected and analyzed. This process involves automatically extracting data from silos and centralizing it in a cloud data warehouse or other destination, where it can be efficiently analyzed. That will facilitate activities like making data-driven decisions on the fly or generating insights from recognized revenue channels.

Ultimately, digital transformation in finance analytics will support high-value projects like dynamic process simulation, predictive performance analytics, and improved machine learning for more accurate forecasting. Automated data integration improves revenue forecasting by ensuring that you have the most up-to-date data in your warehouse. It also helps ensure that your balance sheet and income statements are accurate — instead of pulling transactions manually, which creates a significant time lag, you can access and analyze them in near real time.

Financial Startup Improves Analytics by Simplifying Data Integration

The collection of technologies that digital transformation depends on is known as the “modern data stack”: a fully managed ELT data pipeline, a cloud-based warehouse or data lake, a data transformation tool, and a BI or data visualization platform. A modern data stack gives your finance analytics team access to a constant stream of accurate, up-to-date and standardized data. Automating the data engineering behind finance analytics will free up your analysts to focus on pulling insights from the data, instead of finding, cleaning and transforming it.

Blend is a financial technology startup that has enabled financial services firms to process nearly $1.4 trillion in loan applications and to handle, on average, more than $5 billion in transactions every day. When Blend decided to automate data integration and adopt a modern data stack, it saw amazing results.

Initially, Blend used Redshift as the core of its analytics operations, but its data integration efforts were inefficient and time-consuming. The team was pulling single columns from Salesforce, which was taking weeks at a time, while also attempting to integrate Salesforce, Marketo and Asana into its business suite.

After Blend decided to automate its data integration with Fivetran and use Hightouch for reverse ETL, it saw significant gains in efficiency. Its finance department was able to close out service team books four days earlier than they had in the past, cutting the team’s financial reporting time in half. The team was also able to merge multiple data sources and provide business-wide data analysis.

William Tsu, Customer Success Operations Manager at Blend, said this about transitioning to a more modern, automated finance analytics solution:

The value of Fivetran isn’t in any one individual connector — the value is being able to pull in Salesforce, Marketo, Asana, NetSuite and Lever and blend the data from historically separate departments together for analysis. With Hightouch, we can then push it out to make sure that everyone’s looking at the same metrics.

How to Digitally Transform Your Finance Analytics

Fivetran enables your finance analytics team to effortlessly transfer data from hundreds of applications into a data warehouse or other destination, and then perform managed in-warehouse transformations. The other tools in a modern data stack — cloud data warehouse and BI tool — enable you to run lightning-fast queries and easily visualize and share insights. 

If you’re interested in learning more about Fivetran automated data integration and the potential of a modern data stack to improve finance analytics, please schedule a consultation with our team, or go ahead and start a free 14-day trial.

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