Business Intelligence – How Does Automation Help Data Analysis

Data and business intelligence. It is key for most organizations to get more value from data, make better decisions, and act on it faster. How can process automation help you unleash the full potential of data analytics and business intelligence (BI)? Let’s see it. Large volumes of data, both structured and unstructured, are generated in the day-to-day running of a business.

When we talk about business intelligence, we refer to using data in a company to facilitate decision-making. It is about covering the operation of the entity, with anticipation of future events. The objective? Have the knowledge to support business decisions.

Therefore, extracting new values ​​and insights from business data is key to delivering actionable intelligence to the company’s entire workforce. There are several points where automation can help an entity to get the most out of its data analysis and business intelligence, as we have outlined below.

Data Quality

The use of erroneous data in analytics and predictive models leads to problems related to loss of confidence and financial impact on the business. The data collected helps identify quality problems before analysis. It is a very time-consuming task. In most companies, professionals spend more hours extracting, preparing, and managing information than analyzing it.

How can automation help in this task? This significantly reduces the time analysts spend preparing and cleaning data. The intervention of professionals in this process is limited to controls and final supervision, dedicating their day to other tasks of more excellent value for the company.

The technology RPA allows any number of repetitive tasks to ensure the quality of the data, to the time that automates advanced processes such as scanning and data collection. Document data extraction and document synchronization are two common ways to automate data management.

Data Analysis From Any System

One of the advantages offered by RPA technology is its integration with other systems that are already in operation in the organization (ERP, in-house design, applications). This enables the scope of business intelligence data and analytical tools to be extended to legacy systems, virtualized environments, and systems without APIs.

Automation can help by extracting and analyzing central financial information and collecting exchange rate data from a website in a format that analysis tools can understand. The combination of RPA with artificial intelligence (AI) goes one step further and enables softbots to ‘manage’ unstructured data such as emails, PDFs, images, handwriting, and scanned documents for analysis.
Unstructured data is compiled into a single document (spreadsheet or database) and is ready for analysis in minutes. This allows companies to drastically reduce the workforce’s hours to these tasks, with the consequent impact on productivity and cost savings for their finances.

Decision Making

The decision to turn them into action is the last phase of the data analysis part, where the professional acts based on the analysis in the BI platform. Detects that there are few units left of a given product. Directly from the program, you can activate a purchase order to restock that item. 

Similarly, an IT systems administrator can start a software robot to review stock and detect incidents without leaving the IT service administration dashboard. These are some use cases, but RPA technology enables other high-impact actions in supply chain management, logistics teams, suppliers, finance, and accounting.

Use Business Intelligence Data In More Complex Automations

Companies are increasingly using data science and analytics to gain insights about their business and make more confident decisions. For example, the finance department can report and act on the credit of invoices that are about to meet payment deadlines. Automating the collection of BI data and then using that data for more complex business processes helps organizations make better decisions faster.

Why Implement Automation In Business Intelligence

What are the advantages for a company to apply automation in the management of BI data? With the implementation of software robots for this task, companies get their professionals to have more time to analyze. Therefore, they can make better decisions, act faster with quality information and avoid making mistakes that take a toll on the—company accounts.