Structured and Unstructured Data: Examples and How to Automate

Working with Structured and Unstructured Data

Data is the lifeblood of an organization in the digital age, and finance is at the heart of it. The data you need is typically siloed in disparate systems, making it difficult to aggregate efficiently. In some cases, it requires specific administrative access or involvement from IT to track down. 

Business and finance processes require structure to make the outputs repeatable and scalable, while providing the necessary insight to guide the company. The same holds true for your data. In this post, we will walk through the pitfalls of unstructured data and how you can automate structured data to eliminate time-consuming manual efforts that take capacity away from more value-added reporting and analysis. 

Structured and Unstructured Data Set Examples

To better understand structured data, you need to first realize that data comes in many different forms and complexities. It’s a seemingly endless list that could refer to transaction details, images, compressed codecs, dates, etc. 

Simply put, structured data is quantitative data that is formatted for reporting and analysis use cases, whereas unstructured data is a form of raw data that is not readily set for consumption. Unstructured data requires additional manipulation and classification to be used in a given format. 

Structured data is typically stored in a data warehouse, since it can be centralized from multiple sources and utilizes defined formats, as is the case with accounting and finance. 

If you wish to learn more about data warehouses, lakes and other applicable technical financial operations, check out our post on strategic FP&A best practices

Financial data stored in your general ledger follows a certain categorization, which can be set up during implementation or configured at any point after. It’s best to mirror this after your Chart of Accounts (COA), so if you don’t have a detailed COA, you will want to prioritize organizing that as well. Without fundamental accounting principles in place, you will struggle to fulfill your financial planning and analysis obligations. 

For example, you might sell widgets at multiple store locations as well as direct to consumer (DTC), and therefore, your accounts will have a department or location classification to keep revenue and other financial records organized. 

TIps for Finance Executives and CFOs

Unstructured Data Processing and Manual Data Aggregation

In the past, data processing was an entirely manual process, which was not only time-consuming, but prone to costly errors. Problems typically arise when you wish to work with your financial data from your general ledger to create reports and analyze them for planning and forecasting purposes. 

Messy data requires a thorough pre-processing step that usually falls squarely on the shoulders of accounting and finance professionals. It’s an unavoidable task if you wish to generate accurate financial statements, reporting packages and other scenario analyses. 

The issues compound during every finance professional’s favorite time of year — budgeting season. To develop a detailed budget and targets for the next fiscal year, you need data from disparate systems such as your ERP for financial data, as well as your CRM and HR system for operational data. 

Taking the time to manually aggregate all of your data and munging it together in your spreadsheets is a laborious process that will keep you awake at night, and away from your loved ones on Saturdays. 

Recognizing this mundane manual process, vendors such as FutureView Systems, developed integrations and automation tools to provide the structuring for you. It’s a form of robotic processing automation (RPA), which we will spare you the details of, but recognize that your financial data can be made available, structured and reconciled on demand and at your fingertips. 

Examples of Structured Data and Automations

Here’s a process accounting and finance users are all too familiar with. Let’s say you need to create a financial summary report with specific revenue analysis criteria weekly for your management team and investors. 

You begin by logging in to your ERP, such as Netsuite, exporting your financial data and manually importing it into Excel, your go-to resource to satisfy this request. Unfortunately, the financial data you export is surely unstructured. What exactly does this mean?

Once imported into your spreadsheet, the result is messy data with items in the wrong columns, empty or partial rows of data, name errors, value errors, and well, you get the idea. Even with a few tricks to speed up the process, manually structuring your financial data for reporting and analysis takes hours, time and time again.

The hours you spend each day manually processing this data eat away at capacity for you to conduct deep analysis that leads to strategic and actionable insight for the business. This is an example of how unstructured data can be problematic for finance. 

Tools That Make You a More Valuable Asset

With the help of robotics processing automation (RPA), repetitive tasks and errors can be eliminated. The experienced FP&A and finance professionals at FutureView designed a tool that integrates directly with your ERP, and not only automatically extracts the data, but transforms and formats it for immediate use in Excel via an add-in. We refer to this valuable data automation solution as, FutureView Foundation. 

To remain competitive, companies, especially those that are expiring rapid growth, must remain agile. Relying on antiquated finance processes such as manual data aggregation and processing has a direct impact on the opportunity cost for finance to deliver financial and operational insight that drives strategic conversations by decision-makers and management. 

Without quality and structured data, you’ll never be able to develop your pivot tables, reports and models correctly, and free from error. Remember, Finance must take the data, make sense of it, present it visually and most importantly, provide an explanation that is easily understood.

The ability to leverage tools and quickly assess, pivot and implement change is what allows companies to accelerate their output, ensure greater value and ultimately, operate like a mature finance function. 

If you’re looking for a solution to automate your data processing and financial reporting, Foundation is a fit for you. The direct integration with your ERP, like Netsuite and Quickbooks Online, will be set up for you, and you can use our Finance Excel Add-in to consume dynamic  data in real time.

Give structure to your unstructured data for finance automatically