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In certain sectors like banking, financial services, and insurance, legacy data is still extremely critical. To make data-driven decisions, business leaders are looking to analyze a combination of real-time data, near-term data, and legacy data to make business decisions. They want to compare trends, spot patterns, and take calculated decisions around what worked and what didn’t over the long and short term.
However, the process of garnering insights from different data sets is not easy. For all you know, your real-time data (and near-term data) is probably accessible from Oracle Fusion Cloud, but your legacy data may be stored in Oracle E-Business Suite (Oracle EBS) or PeopleSoft, or maybe another ERP or custom applications which your company used a while back.
There may also be a case where an enterprise may have grown through acquisitions, and in such scenarios – legacy data from the various companies acquired may be residing in different applications.
In this Ultimate Guide, we’ll help you answer several questions about the value of legacy data, how to combine past and present data to get better intelligence, and why we need a modern reporting solution for Legacy Data reporting.
Earlier this year, we wrote a detailed post on ‘Combined Financial Reporting from Oracle Fusion Financials Cloud ERP and Oracle EBS after Migrating to Cloud ERP’.
Read it here: https://www.orbitanalytics.com/combined-financial-reporting-from-oracle-fusion-financials-cloud-erp-and-oracle-ebs-after-migrating-to-cloud-erp/
Legacy data, also known as historical data, is valuable because it provides a record of past events, trends, and patterns. This data can be used to gain insights into how a business has performed over time and can inform future decision-making.
Here are some reasons why legacy data is valuable:
Identify Trends, Patterns & Gaps: Legacy data can be used to identify trends and patterns that have emerged over time. This can help decision-makers to understand how the business has evolved and identify areas where improvements can be made.
Use Legacy Data to Build Predictive Analytics Models: By analyzing legacy data, businesses can develop predictive models that help them to forecast future trends and patterns. This can help decision-makers to make more informed decisions about future investments and business strategies.
Compliance requirements: Many industries are subject to strict compliance and legal requirements. Legacy data can be used to demonstrate compliance with these requirements and provide evidence in legal disputes.
To use legacy data effectively, decision-makers need to ensure that it is accurate, complete, and up-to-date. They should also be aware of any limitations or biases in the data and use it in conjunction with real-time data and present data to ensure that their decisions are based on a comprehensive understanding of the business.
In addition, decision-makers should use data visualization tools to help them make sense of the data and identify trends and patterns. They should also consider using machine learning and other advanced analytics techniques to gain deeper insights into the data and develop predictive models.
Ultimately, the key to using legacy data effectively is to view it as a valuable resource that can inform decision-making and help businesses to achieve their goals. By combining legacy data with real-time data and present data, decision-makers can gain a more comprehensive understanding of the business and make more informed decisions about its future.
There are several sectors that need to store legacy data for compliance reasons. The length of time that data needs to be stored depends on the specific regulatory requirements of each industry.
Some examples are below:
Healthcare: Healthcare providers are required to store patient medical records for a certain period of time. The length of time varies depending on the state or country, but it is usually several years. In the United States, the Health Insurance Portability and Accountability Act (HIPAA) requires that medical records be retained for a minimum of six years from the date of creation or the date when they were last in effect.
Banking, Financial Services & Insurance: The BFSI industry is subject to numerous regulations that require the retention of certain types of data for specific periods of time. For example, in the United States, the Securities and Exchange Commission (SEC) requires that broker-dealers retain certain records for three to six years, depending on the type of record.
School Systems & Universities: Schools and universities are required to retain student records for a certain period of time. In this sector too – the length of time varies depending on the state or country, but it is usually several years. In the United States, the Family Educational Rights and Privacy Act (FERPA) requires that educational records be retained for at least five years after the student leaves the institution.
Public Sector & Government: Government agencies at the federal, state, and local levels are required to retain certain types of data for specific periods of time. For example, in the United States, the National Archives and Records Administration (NARA) sets standards for the retention of government records, including emails, financial records, and personnel records. In general, the retention period for legacy data in these sectors is driven by regulatory requirements aimed at protecting individuals’ privacy, ensuring financial transparency, or preserving important historical information. It is important for organizations to comply with these regulations and to have a clear understanding of the retention requirements for their specific industry.
Enterprises can use legacy data in combination with present data to get a comprehensive understanding of their business performance, trends, and customer behavior.
Here are some examples of how this can be done in the retail sector:
Pricing optimization: By analyzing legacy pricing data, retailers can identify trends and patterns in their pricing strategy. They can then combine this data with real-time and present data, such as competitor pricing and customer demand, to optimize their pricing strategy. This can help retailers to maximize revenue and profitability while remaining competitive in the market.
Sales forecasting: By analyzing legacy sales data, retailers can identify trends and patterns in their sales performance. They can then combine this data with real-time sales data and present data, such as inventory levels and marketing campaigns, to develop more accurate sales forecasts. This can help retailers to optimize their inventory levels, reduce stockouts, and improve customer satisfaction.
Customer segmentation: Legacy data can be used to segment customers based on their past behavior and preferences. Retailers can then combine this data with real-time and present data, such as website clicks, social media activity, and in-store behavior, to create a more complete picture of their customers. This can help retailers to personalize their marketing messages, improve customer retention, and increase sales.
Product recommendations: Legacy data can be used to analyze customers’ past purchase history and preferences to make personalized product recommendations. Retailers can then combine this data with real-time data, such as website clicks and search queries, to make real-time recommendations that are relevant to the customer’s current interests. This can improve the customer experience and increase sales.
By combining legacy data with present data and real-time data, retailers can gain a competitive advantage in the market and improve their overall performance. It can also be used to build more effective advanced analytical models.
Legacy data reporting refers to the process of analyzing and reporting past data. The first step is to extract data from multiple sources – where legacy data resides.
One use case for legacy data reporting is to help answer very specific questions based on past data. For example, the data can be used to answer specific questions, such as:
By analyzing legacy data and generating reports, businesses can gain a better understanding of their historical performance and make data-driven decisions that are informed by past trends and patterns. This can help them to identify areas of opportunity and make more accurate predictions about future performance.
As companies migrate from Oracle E-Business Suite (Oracle EBS) to Oracle Fusion Cloud Applications an important decision that comes into question is:
How do we handle legacy data residing in applications like Oracle EBS? It’s an important question to answer for the following reasons:
Orbit’s Legacy Data Reporting Solution makes it easy for business users to do self-service operational and financial reporting from legacy data residing in Oracle EBS.
How do you decide which legacy data reporting tool to invest in? What are the key factors to consider?
At Orbit, we put together a checklist on this topic, and we republish it here:
Here’s a common scenario at several enterprises. As part of their cloud migration strategy, companies are making the move from Oracle E-Business Suite (EBS) to Oracle Cloud ERP Solutions. They are migrating limited data to Oracle Fusion, with the plan of keeping both ERP systems (EBS and Fusion) up and running. However, this is a challenge – both in terms of maintenance effort and costs. With a solution like Orbit, you can run reports from both data sources – legacy data in EBS and current data in Oracle Cloud ERP – without keeping Oracle E-Business suite up and running. This is a major advantage for companies.
For a more detailed perspective on this topic, read this blog:
Orbit offers a modern reporting tool that is ideal for operational reporting, financial reporting, ad-hoc reporting, and analytics. Today, business leaders are looking for a reporting solution that is truly self-service. They want to reduce the burden on IT teams, so they can drive agility into the process of generating reports.
Several customers around the world – from Fortune 500 companies to fast-growing startups – choose Orbit for Legacy Data Reporting even as they migrate to Cloud ERP solutions like Oracle Fusion Applications.
For information, visit: https://www.orbitanalytics.com/legacy-data-reporting-for-oracle-ebs-data/