Data Quality Is Key for Effective Crisis Response
The COVID-19 pandemic has had a dramatic impact on society worldwide. The emotional and economic damage will be felt for a long time. And the crisis is still evolving, with some countries opening up and staff returning to their offices only to close down again or restrict movement.
As employees adjust the way they work and experience a changing dynamic in their home life, they have turned to their company leaders for guidance as they see them as a trusted source. Communicating with employees during a crisis should not be about sending out details on company policy or just sending general updates; it should be used as an opportunity to boost morale, motivate, inspire, and ensure the safety of employees.
During a crisis, not everybody will have access to a laptop or tablet; however, you may need to contact employees by phone call or SMS. Similarly, you will need to know the exact location of your employees during a crisis, such as after a natural disaster. After the initial chaos, you will need to know your communications are being received either by email or phone or via a postal service.
But for many businesses, employee contact data may be scattered across the organization, incomplete, or not verified for accuracy or deliverability. This limits an organization’s ability to communicate effectively across multiple channels.
Providing a Trusted Foundation for Decision-Making
Before the advent of COVID-19, the volume of data gathered by healthcare organizations was accelerating. They rely on data for operational and financial planning, workload balancing, clinical decisions, scientific studies, and to identify trends. However, the current pandemic has increased the volume of data and brought the need for high-quality data into sharper focus. Healthcare professionals, government agencies, higher education institutions, and businesses are looking for ways to use that data to make faster and better decisions in response to the crisis: How do we optimize resources? Can we identify potential infection clusters? How do we perform contact tracing? All of these decisions have to be made at speed.
Another area of concern in a crisis is fraud. There are a lot of unscrupulous actors who might take advantage of the chaos and uncertainty. While many organizations have implemented anti-fraud technology, they are still having challenges optimizing performance related to data quality. As the saying goes, “Garbage in, garbage out!”
That’s why data quality is so critical to delivering trusted insights. Bringing together insights across different data sources—structured and unstructured, static and streaming, each with its own data schema—puts a high demand on the quality of the data being combined. And the more complex the data, the bigger the risk that it’s incomplete, inconsistent, or inaccurate.
As noted above, the quality of data can have a significant impact on how you engage with employees and make timely decisions in a crisis. But managing data quality can be a big job that involves repetitive work.
Accelerating Data Quality
With Informatica Data Quality, you can create data quality rules to identify anomalies in your data, fix the data, and continuously monitor the quality of the data. These rules can take time to develop. By deploying predefined data quality accelerators, you can quickly deliver trusted data that is fit for purpose promptly.
The free Informatica Data Quality Accelerator for Crisis Response meets the challenges that crises and emergency management bring to data handling, contact verification, and decision-making. The accelerator adds business rules to your Informatica environment that speed up data analysis, improve data quality and contact efficiency, and enable you to track patients, diagnoses, outcomes, and healthcare issues.
The rules address the most common data quality issues, with a focus on issues that can arise in healthcare, government agencies, higher education, and business. Use the rules to quickly implement a data quality strategy that can make your data more reliable and useful. The rules are ready to use out of the box. You can customize the rules to suit your data requirements.
The Data Quality Accelerator for Crisis Response includes rules that perform the following tasks:
- Discover:Discover facts about your data—for example, determine the level of completeness in your columns, and establish the conformity of the column data to the structures and types of data that you expect.
- Standardize and Cleanse: Standardize the form and structure of common data values, such as dates, telephone numbers, addresses, Social Security numbers, and country identifiers. Additionally, standardize the use of character case and diacritic characters in the data. You can also remove extraneous symbols, characters, and character spaces from the data.
- Calculate and Identify: Calculate and derive a range of facts from your source data, including patient age, gender, time elapsed since diagnosis or other milestones, physical distance from a given location, and presence within a given target area.
- Parse:Parse important data values from fields that contain strings or multiple values. For example, parse telephone numbers, CPT codes, comorbidity factors, Social Security numbers, and healthcare facility types from source data fields, and write each type of value to a discrete new field.
- Match:Identify records that contain significant duplicate information, so that you can fix or remove the duplicate records. Match rules analyze the information that the records represent and therefore can find duplicates when records are non-identical.
- Validate:Verify that your data is accurate or present in the expected form. You can validate medical data, such as principal diagnoses, CPT codes, and ICD-10 data. You can also validate common business and personal data, such as patient ages, state names, and ZIP codes.
In a time of crisis, you need to act fast and make decisions even faster. The last thing you want is to have poor-quality data slowing you down.
Learn more about the free Informatica Data Quality Accelerator for Crisis Response.
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