 hello and welcome to the session in which we will discuss data quality. So what is quality? Quality is how good something is and how good is the data. Now why is data quality important? Well because high quality data is critical, is essential for making informed decision because we're analyzing data trends and patterns and ensuring that the data driven outcome are accurate and trustworthy. So if the data is no good, your outcome, your business decision is useless. So that's why the quality of the data is important. And what does quality refer to specifically? It's the overall value and usefulness of the data and it can be evaluated through three dimension, three dimensions. We're going to look at the data intrinsic quality and we're going to explain what does that mean. We're going to look at the data contextual quality and we're going to look at the security accessibility quality of the data. So once we explain those three concepts as they relate to data quality, we will have an overview of what data quality would look like. Before we proceed any further, I have a public announcement about my company farhatlectures.com. Farhat Accounting Lectures is a supplemental educational tool that's going to help you with your CPA exam preparation as well as your accounting courses. My CPA material is aligned with your CPA review course such as Becker, Roger, Wiley, Gleam, Miles. My accounting courses are aligned with your accounting courses broken down by chapter and topics. My resources consist of lectures, multiple choice questions, true-false questions, as well as exercises. Go ahead, start your free trial today. No obligation, no credit card required. Starting with intrinsic value or intrinsic data quality. What is that? It's a measure of the inherent accuracy, completeness, consistency, and relevance of the data. For the data to have intrinsic value, it has to have those four components starting with accuracy and we should all know what accuracy is. Well, does the data that we are using accurately reflect the real-world phenomenon it represents? So is it reflecting what it's supposed to reflect? For example, if a database contains customer information, the customer name, address, and phone number should be accurate and up-to-date. Is it accurate? That's the first thing. Two, completeness, the degree to which the data contains all the information that's necessary for whatever we are using it for that specific case use. For example, going back to the customer data, well, the customer's record should contain all required fields such as name, address, phone number, and email. Let's assume we're analyzing addresses and we don't have all the addresses. The field is missing. The data is considered incomplete. It's of a low quality data. Consistency. What is consistency? The degree to which the data can form to the same standard. You all have the same data, formatted the same way. It has the same definition. The address field is actually an address. A phone number is actually a phone number and formatted across different sources. What could happen is a company could have multiple databases that store customer information and the data should be consistent across all databases with the same definition, formatting, and similar data elements. So that's why consistency is important because you could be using data from different sources. If it's consistent, it's easy to consistent not only in terms of the structure, in terms of the data definition, in terms of the field relevance. The fourth intrinsic value concept is the degree to which the data is useful. Is it relevant for us? Whatever we are doing, is it good for our business case, our business decision improving intrinsic data quality required continuous data cleaning because the data has to be clean. Clean will give you accuracy. You validate the data, make sure it's complete. It's standardized. So it's consistent to ensure that the data accurately reflect the real world for what's intended to use. For example, the data about customer who have not made a purchase in the past 12 months may not be relevant for a marketing campaign targeting active users. It's not relevant for us. It's not relevant. Why? Because it's too old. So the data should be relevant to the specific case and we're going to see timeliness later on, but relevant also in terms of time. The second value is contextual value or the contextual quality of the data. This referred to the suitability. Is the data suitable for our specific context or use or our decision taken into account factors such as data source? Is the source of the data good for us? Data format, data timeliness, which we talked about timeliness in the prior session. It's part of contextual quality as well. Data source. We have to look at where is the data coming from, the origin of the data and the method we collected the data impact its suitability. How good is the data? For example, we could have data collected through surveys may not be as reliable as data collected through experiments because the user don't know the purpose. Therefore, they cannot answer in a specific way. Data format. The format in which the data is stored and presented can impact its suitability. For example, structured data, data and spreadsheets and databases are much easier because it has a better format to use for analysis rather than data that you can find in a text. Three, data timeliness. And we spoke about this on the prior slide. The age of the data is important. For example, data about the company financial performance from five years ago may not be relevant for today for a current business decision. Therefore, also the time is important. How recent is the data? In order to ensure high contextual quality, data should be collected from reliable sources as reliable as possible, stored in appropriate format and kept up to date to ensure its suitability for our business use. The third component of data quality is security and accessibility quality. Well, the word security and accessibility tells it tells it all. Security is the level of protection from unauthorized access, modification, deletion, as well as the accessibility of all data to all authorized users. What is security? Well, the measures put in place to protect the data, protected it from what? From unauthorized access, modification, or deletion. How? You can encrypt the data, have access controlled, make sure you have a backup and disaster recovery procedures because that's part of the security. Accessibility means what? The ease which authorized users, all authorized users can access and use the data. This includes factors such as availability. Is it available? The technology used to access the data and the skills of and training of the users. For example, a company should provide training and support for employee how to access the data and how to use the customer data. The company also ensure that the data is available 24-7 and that employee can access it from any location as long as it's a secure connection. Also, this includes a regular reviews and update about security measures because people hacking you, they always try different things. They always try different technology. You need to provide training and support, continuous training and support to the employees to ensure that technology used to access the data is up-to-date and reliable. What should you do now? Go to Farhat Lectures and look at additional resources, multiple choice that's going to help you understand the concept of data quality. Study hard whether you are studying for your CPA exam, CMA exam, CISA or Accounting Information System course. Invest in yourself, invest in your career and stay safe.