Data Deduplication for Government Agencies: Risks and Solutions

For most companies, duplicate entries can signal warning signs of potential missed revenue targets, negative brand perception, and poor campaign response. For government agencies, however, it can mean the inability to manage the growing strain on virtual machines or storage hardware and disaster recovery and backup initiatives which could otherwise cost substantial amounts of financial losses.

Deduplication, for this reason, is critical to not only withstand the growing volumes of public sector information but also allow agencies to achieve cost-efficiencies to sustain day-to-day operations.

In this post, we’ll look at the problem of duplicate data and how a dedupe software can be used in resolving it.

What Does Data Deduplication Mean for Public Institutions?

Data deduplication refers to the process of removing duplicate and redundant copies of unique records to minimize storage space and reconcile conflicting records. Data deduplication helps organizations ensure that they only have one master record or value for processing that cuts their data footprint and ultimately storage costs.

Through deduplication, companies can identify and dedupe all repeated values from disparate and multiple data sources including databases, Excel, web applications and even APIs. For more info, check out the data deduplication guide.

Why is Data Quality Critical for Agencies?

Data quality is of critical importance to federal agencies owing to the Data Quality Act (DQA) made effective in 2000. Successive governments have intensified the quality standards along with other mandates such as the Open Government Initiative and Data Center Optimization Drive to ensure any data that is shared and disseminated is accurate.

The DQA mandates that any federal agency’s data conform to the highest quality standards and meet the following three guidelines:

  • Utility: the information shared or disseminated is useful and relevant to the end user.
  • Integrity: the information is not shared without authorization and is not corrupted or falsified.
  • Objectivity: the information presented should be accurate, complete, and reliable to the end user.

Furthermore, having clean and accurate data is critical for achieving various business objectives. For example:

  • Transparent and reliable data can prevent agencies from making improper payments to contractors
  • Agencies tasked with regulation can better enforce regulations by having up-to-date and duplicate free data.
  • Funding and grant allocation can also be more streamline with efficient entity resolution and record linkage processes

For these reasons, federal agencies need to ensure their data is free from errors including duplicate values for them to comply with the guidelines.

Consequences of Duplicate Data

Although legislative measures can push agencies to adopt more stringent measures of improving data, achieving it can be a major challenge; the presence of legacy systems, disparate data sources, and siloed information can lead to duplicate records piling up.

Here are a few challenges that duplicate data can create if not addressed:

  • Higher storage costs: duplicate entries increase the data footprint within systems which increase storage capacity requirements. This can eventually lead agencies to purchase additional hardware that can shoot up overhead costs.
  • Increases backup capacity requirements: having more copies of unique records places greater strain on backup windows. This can slow down the speed at which records can be retrieved that can also place strain on virtual machines.
  • Greater exposure to disasters: since agencies will have more redundant and repeated records to process, creating backups quickly will become challenging, effectively exposing them to a DDoS attack, data center outages and hardware failures, and more.
  • Increased cycle time: more records can cause a surge in bandwidth as more data will be passed along the network that can increase the time taken to process records and retain data.
  • Mismanagement of funds: without accurate data, agencies can fail to have proper insight into actual financial and accounting data and lead to overpayment to contractors, under or over reporting, and delayed collections from debtors.

How Does a Dedupe Software Address Duplication Challenges?

According to CTOLabs.com, nearly 9 out of 10 federal agencies viewed data deduplication as a high priority and data retention and recovery were the biggest concerns.

A dedupe software can act as a powerful tool to help organizations minimize storage capacity requirements by minimizing or eliminating redundant records and reconcile conflicting identities.

Under the right framework, strategy and roadmap, a deduping software can enable agencies to achieve the following:

  • Identify and fix erroneous records: sophisticated data profiling, cleansing, and standardization features can enable agencies to locate duplicate as well as missing,
  • Remove duplicates across multiple systems: when managing data across disparate sources, it is possible for duplicate and redundant records to creep into other sources. Thus, deduping tools can connect to various source systems and ensure any deduplication process is thorough enough to include all possible sources.
  • Save time: finding and removing duplicate records can be a painstakingly long process comprising of several days. A dedicated dedupe software, however, can find repeated values of records and remove them within only a few hours.

Example of Deduplication in a Federal Agency

The Department of Justice (DOJ) receive and process thousands of FOIA requests, each of which has to be properly interpreted, communicated with the requestor, and thoroughly researched. Using a deduplication software, the agency was able to reduce a field from 4 million to 3 million records, which were further minimized to 4,000 records upon filtering. The entire deduplication activity lasted just four hours which otherwise would have taken several weeks if done manually.

Deduping Records Using DataMatch Enterprise

Data Ladder’s DataMatch Enterprise (DME) is an industrial-strength matching and deduplication tool designed to reconcile unresolved entities and dedupe redundant and repeated records to help agencies considerably cut their data footprint.

For more information on using DME as a dedupe software to find and remove duplicates, feel free to get in touch with us today.

Fahad is a Product Marketing Manager at Data Ladder. Combining his background in marketing and experience in sales and content, Fahad aims to deliver consistent, quality messaging across all platforms to influence product sales.

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