Financial reports and data are at the core of every business because they are part of reporting and decision making for all departments, as we mentioned in our previous blog “How Finance and Marketing Can Work Together to Use Data.” Companies need to become analytically mature by moving away from localized analytics toward a centralized approach that enables the sharing of financial data across the business.
In a briefing paper, Harvard Business Review stated that becoming analytically mature requires that a business go through 5 stages of becoming an insight-driven organization:
- Analytics Awareness
- Localized Analytics
- Analytical Aspirations
- Analytical Companies
- Analytical Competitors
Companies need the right infrastructure and skill sets to get through all 5 stages and achieve the goal of data maturity.
dbSeer and Amazon Web Services (AWS) help companies achieve analytical maturity faster and more cost-efficiently by providing the infrastructure required to build a centralized data platform for financial analytics in the cloud.
Table of Contents
Moving Beyond Analytics Awareness
In the first stage of analytics maturity, companies know about analytics but either have inadequate or no infrastructure in place to support them. Companies at the first stage also lack a defined analytics strategy.
Without the proper infrastructure or strategy, these organizations can’t harness the value of real-time data. To become truly data-driven, companies need to have goals in mind for what they want to achieve with analytics.
AWS cloud can provide the necessary infrastructure to get started with analytics and realize an analytics strategy. With AWS, companies can set up their infrastructure in a matter of days without the need for a lengthy procurement process. Setting up cloud infrastructure for a data platform requires no initial investment. Instead, companies pay as they go and only pay for what they use.
Centralizing Localized Analytics
During the second stage, finance departments know they need to perform limited data management on a departmental or application level. These localized analytics may be performed as needed.
However, companies at the second stage of analytics maturity lack the centralized analytics needed to share financial data and reports across departments. These companies need a way to store data in a centralized location so that every department has a single source of truth on which to base decisions.
AWS can provide this centralized location through data lakes and data warehousing, allowing a company to move to the next stage of maturity quickly. The existing architectural framework allows for a fast and secure implementation.
Realizing Analytical Aspirations
At the third stage, companies are looking beyond localized analytics to a more widespread and centralized approach so all departments can leverage financial data. The stage of analytical aspirations involves expanding limited analytical capabilities beyond data and reporting silos and into mainstream business functions.
AWS cloud enables organizations to realize their analytical aspirations by putting the right infrastructure and analytics capabilities in place. Other solutions, such as Microsoft Power BI for data visualization, can connect to the centralized data platform for an integrated approach to analytics.
Becoming Analytical Companies
By the fourth stage of maturity, a business is turning into an analytical company. Analytical companies combine data from sources in finance with information from other departments to create meaningful reports and reach deeper insights.
AWS cloud data warehousing and data lakes give companies a place to store financial and other types of data so it can be shared between departments and analyzed for real-time insights.
Transforming Into Analytical Competitors
At the last stage of analytical maturity, the business has become a strong competitor through analytics. Analytical competitors rely on advanced analytics, including artificial intelligence (AI) and machine learning (ML).
These advanced analytics capabilities help the company manage performance, maintain value, and create new sources of value while keeping up with the evolutionary pace of technology change.
Companies at the highest level of analytics maturity empower employees in any department or job role to use financial data to make business decisions. When companies reach stage 5, they have become truly data and insight-driven organizations.
AWS cloud provides managed services to build, train, and deploy ML models that include infrastructure, tools, and workflows.
CONCLUSION: Accelerating Data Analytics Maturity
When companies combine data lakes and warehouses with AI and ML, they have all they need to reach the final stage of analytics maturity. By adopting AWS, organizations can fast-track themselves to analytics maturity by acquiring a cost-effective and easily scalable infrastructure.
AWS cloud automates capabilities for building and managing data warehouses and data lakes along with the advanced analytics services needed to gain deep insights from both structured and unstructured data.
dbSeer has achieved Advanced Consulting Partner status in the Amazon Web Services (AWS) Partner Network (APN). As an AWS Advanced Partner, dbSeer’s AWS Certified professionals help clients with AWS database migration and data warehouse design, as well as the process of building big data analytics applications. Our team can help your business use AWS cloud to build financial analytics and accelerate your path to analytics maturity.
Does your company need to increase its level of analytical maturity? Reach out to dbSeer today to find out how we can get you to the top level.
