 Hello and welcome to the session in which we will discuss data governance, but first we need to discuss Data and what is the source of the data and now we have this term big data. Where is this data coming from? Well, the rise of data is driven by advancement in technology Such as the use of smartphone and internet connected devices the growth of the internet and social media Anywhere you click you make a comment. You like something There is data collected by these social media companies or internet companies That is recording this data and trying to make a decision based on your behavior This led to the importance of data management and data governance for achieving business success So your usage of the internet you think Facebook is free. Yes, you are using Facebook for free however They're collecting the data to learn about you as an individual as well as you and Profiling you and million of other users to be able to market Product and services to you the aim of data governance is to transform large and filtered pooled of data Into some sort of a structured useful data That can be used to solve business problem. So think about all the clicks the likes The visitation of pages. How long you stay on a certain page? What time you visited who are your friends? Who did you speak to where did you comment? All of this taken together is unfiltered pooled of data. It's a bunch of data that don't make any sense The key is to turn it into a structured data where it becomes useful and it's being used for business decision So business process generates data when you use the internet it's gonna generate data then what we're gonna do we're gonna take this data and We're gonna use data governance Management and analysis to turn this data into a valuable business insight and would look something like this We have a business the business generates data by you by the users when you buy from them visit their website Check out their product then this data It's gonna help the business create insight and create business help the business create business decision Before we proceed any further. I have a public announcement about my company far hat lectures dot com Far hat accounting lectures is a supplemental educational tool That's gonna 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 through false questions as well as exercises Go ahead start your free trial today. No obligation. No credit card required So simply put what is data governance? Well data governance is the overall management Availability usability and integrity as well as the security of data used in the organization because data is important We want to make sure it's available to us. It's useful to us. It has integrity and it's secure This includes what how do you achieve all of these? Well, you have to establish policies and procedures for collecting the data Storing the data using and protecting as well as creating roles and responsibilities for Individuals and group within the organization who are responsible for managing the data And this is what data governance is and what is the goal of all of this? Well, the goal of all of this is to make sure the data is accurate consistent and accessible whoever is need this data and Also being protected from unauthorized use and the overall purpose is for business decision So why do we have data governance? Yes, we want to protect the data. Yes We want to have accurate data But we want to use this data to make a better decision now data governance is not an easy Topic in the real world. We do face challenges in collecting the data Maintaining the data filter filtering the data So we're gonna look at data challenges data governance challenges and we look at some mitigation what companies can do the following are data Governes challenges data silos data quality data security data compliance data privacy data governance structure data Governes automation and scalability. So I'm gonna have this list and every time I have a list I'm gonna go through each term in this list separately to understand to explain What that terms means starting with what are data silos data silos refer to the isolated storage of data in different departments System and platform within organization as silos is when you have different unit Separated separated within a company. This is what data silos is This can make it difficult to establish a centralized view of the organizational data as well as to ensure consistency Accuracy across different data structure or data sources Why because each unit or each department maintain their data separately, so there's no uniform There is no consistency across the data. This could be a challenge to govern the data So when data stores and silos it means each department store their own data separately in a different way It's difficult to manage maintain and ensure the quality of the data Also siloed data can make it difficult to share information across different department and teams Which can lead to an efficiency and delays? Well, what do we need to do to tackle this challenge this data silos? Well, they can implement data governance framework that include guidelines processes and tools for collecting storing and managing the data So basically everyone is on the same page. This include data governance console That tells everybody what they're need to be responsible for data stewardship roles For example in each department, we will have a person saying you are responsible of this data And you're supposed to share the data with the other silo data governance committee to help ensure consistency and coordination Across different data sources because data could be in different places and then in the organization and with different people Also, the organization can use data management and integration basically somehow integrated electronically To help to bring the data together and create a single view of the data's organ of the single view of the organization's data The key here is the data is in a separate silos We want to make sure it's all integrated so we can see the full picture The second challenge of data is data quality. What is data quality? Ensuring the accuracy and completeness of the data. This is what makes the data Good has a good quality. This could be challenging, especially when the data being collected From many multiple sources. So data quality issues can result from a variety of factor Well, starting from data entry if the data entry is incorrect, your data is no good Maybe the data is missing. Maybe the data is inconsistent Or the data could be out of date. All of this will create poor data And what would poor data do? Poor data would lead to a variety of issues Incorrect analysis or decision-making inefficiencies delays as well as a reputational and financial risk. So poor data is really expensive Okay, why because it's gonna let to poor decisions poor business decision What should the company do to mitigate or tackle this challenge? Well, they can implement a data quality management process For example, they can do what's called data profiling data validation and data cleaning Cleansing. Let's see what these are. What's data profiling involve analyzing the data to identify patterns and potential issues Basically profiling something just to see what it looks like make a profile about this data while validation Data validation involved checking the data against set of rules to to ensure it meets certain standard So we receive the data. We want to make sure it's good We have to compare it to something else that makes sense data cleansing basically cleaning the data means removing Or correcting any inaccuracies or consistencies in the data. Sometimes the data is not complete We want to make sure it is complete or whatever there is data. That's really Useless. It doesn't make any sense. We need to correct it and take it out Also, the company can start establish a data quality governance role such as a data quality manager someone who's responsible For making sure the data has quality checking the data data quality stewards to help ensure that data quality is consistent monitored and maintained another important aspect to consider is to have a clear understanding of the data lineage What we mean by the data lineage? It means the history of the data. What does that mean? It means? Where is the data coming from? What is the source of the data and where it's it stored? Okay, where it came where it's coming from. What's the original source? Where did we store it? This will help us understand the data and its quality as well as to identify and correct any issues that might arise if we know The source we can go back to the source and check the data Another issue with data obviously is data security and what does security deals with? Protecting the data from unauthorized use or breaches. Well, that's always a challenge Especially when we have constant cyber attacks these days Why because data breaches can result in lost theft of sensitive information Which could lead to reputational damage? Financial losses legal penalties. What can the company do? Well, they can have data security measures such as data encryption. They can encrypt the data We'll talk about this later on access control means who can or cannot access the data And we'll talk about access control much much more in details later on we have physical we have logical Insecurity monitoring what is data encryption real quick data encryption means use an algorithm to scramble data So in case somebody found it they cannot read it It's unreadable to unauthorized parties because they don't have the keys to unscramble this data What is access control set on up rules and procedures for who can access and use the data using login and monitoring access? We'll talk about that later on as well as data encryption security monitoring involve involving tools and techniques to detect and response to security threat in real time And this is we're talking about cyber security and we'll talk about that later on in a different session Organization can also establish security governance role someone in charge of data security such as the chief information security officers Also, we have data security managers to help ensure that data security is consistent monitored and maintained Another important aspect to consider is to have a comprehensive Comprehensive data governance policy that include identification of sensitive data. So we need to know which one is sensitive data Which one is important data? So we're gonna treat sensitive data with data That's not really as sensitive or as important. Okay, the classification of data and the definition of security measures should be applied to it If this is sensitive data, basically secret top secret or not a secret information. We need to know What are we dealing with? This will help ensure that the appropriate security measures are in place to protect sensitive data and to comply with regulation Another issue we have to deal with when it comes to data as data compliance So organization must comply with a variety of regulation and standard Related to data and some of these regulations could be national like in the US and some of them could be international like think of HIPAA, H-I-P-P-A and what is HIPAA? It's the health insurance portability and accountability act and you need to know more and more about HIPAA when it comes to the CPA exam basically making sure the information of the of the patient is protected from breaches security breaches and privacy issues We also have something called GDPR, which is the general data protection regulation Well, here we're talking about rules that even are implemented or followed in Europe So you have to comply with that because once you're on the internet you're everywhere and Obviously socks in the US which can be difficult to navigate. So your data must be in compliance So these regulations and standards set guidelines of how organization must handle and protect personal and sensitive information Data as well as how they must report data breaches in case something happened. That's important I know a lawyer. I met a lawyer recently that deals with this The data breaches happen much much more often than we think But we don't know about it because businesses never ever you never ever know about the data breach because for reputational purposes Companies don't want you to know you only know about these breaches when it's a publicly traded company because the information has to be public Many many private companies are subject to those data breaches and they go unnoticed Also non-compliance with these regulation can result in hefty penalties hefty penalties, hefty fines and reputational damage That's the worst type of damage. To tackle these challenges the organization can implement data compliance processes Such as data mapping data classification and incident report planning. What what's what's data? What is data mapping involve identifying which data is sensitive that stored and how you it can be used throughout the organization So not all data is equal Certain data is more important than other will talk about data mapping later on as well data classification Involve assigning different level of protection to different types of data based on their sensitivity So after you map it you classify it and you implement the right security measure for this data Incident response. What does that mean? It means planning involve developing procedures for how to respond to data breaches or other incidents So something happened. Well, we have to have certain procedures on how to respond How to how to contain the incidents how to notify the affected parties which could be very, you know Very not not a happy incident for them and how to perform forensic investigation to see what happened and prevent that from happening again Also, the organization can establish data compliance governance rules such as data protection officers or compliance managers to help ensure data compliance is consistent and Monitor another important aspect to consider is to have regular training and awareness for the employees make sure they understand Which data is sensitive? Which data is top secret? Which data is important? Which data is everyone can use to ensure their aware of regulations and the company policies And this will help ensure that the employees understand the responsibilities and the risks associated with this data Another issue related to compliance and security is data privacy with the increase in amount of data being collected stored and shared Organization must be able to protect the privacy of individual and ensure their data being used in a responsible and ethical matter Data privacy is a complex issues because it involves the balancing benefit of data use against the need to protect personal information So organization they must demonstrate Transparency and accountability on how they collect use and share the data and this is an important Concept or important topic for a company like Google to tackle data privacy Organization can implement data privacy processes such as data minimization and data retention What is data minimization? It means collect the data That you only need for a specific purpose no more no less So therefore you limit the amount of data that's being collected and stored and data retention means setting policies for how Long you keep this data and when it's deleted sometime you have to delete it by law Also organization can establish data privacy governance roles such as Data privacy officers or privacy managers to help make sure that data privacy is consistent monitored and maintained Another aspect to consider is a comprehensive data policy that covers data collection How do I get the data? How do I store it and how do I share it? This would also help ensure the organization is transparent and it's handling practices and to comply with the relevant data Privacy data governance structure is ensuring that The data governance is properly aligned with the overall goals and objective of the organization. How do you make sure that's the case? Well You want to make sure you're assigning the proper resources while having enough staff that staff is properly trained You have a budget to effectively implement and maintain the data governance program Because you want to have data governance but if governance but if you don't provide the money the people the resources Then you can't do it so without adequate resources It will be very difficult to achieve the goals of data governance program You also have to have adequate participation from management buy-in from stockholders They have to adopt this getting the support of key decision makers data owners and other stake stakeholders Who play role in data governance think about if the owners of the data don't want to release the data Then there's nothing you can do so you want to convince them It's a good idea to have a comprehensive Policy without these people support it can be very difficult to implement and maintain effective data governance process Also data governance complexity Why you because you might have multiple business areas and data types which mean different or governance processes roles Responsibility may be required think of companies that buy other companies they grow through acquisition They grow through consolidation So they could have all sorts of data and how are you going to collect this data make it uniform clean it? Make sense out of it so it is a challenge Why because you might have different governance process in each company and to consolidate this it may not be an easy process Data governance scalability and automation so as the amount of data Generated by a company grows it can be Increasingly difficult to maintain effective data governance. So the bigger it gets It's gonna be harder and harder to maintain unless you have a good governance structure This include being able to handle this increased volume Velocity and variety of data and we have the V V and V as well as being able to scale the data Governance process and system to meet the organization Changing need and that's why it's important to have a framework because the framework would help you whether you have 10 gigabyte or 10,000 gigabytes of data It's all this also include being able to adapt to new data sources your data will change over time So for example, you're you're getting the data from one source and in a certain way The source might change or the same source could start to provide the data in a different way Such as the Internet of Things and artificial intelligence which can introduce new challenges and complexity Because think about it if you're collecting a data from a website from the Internet of that Internet page that Internet structure Changes then the data you are collecting will change. How would you handle that again? You have to automate the process automating the data governance can help organization to manage large amount of data But it requires a significant investment in technologies and the right skills to implement it It's not easy. So as the data grows, you're gonna have challenges. So as the data grows What is your key response? Have a good governance structure and automate the process We're gonna be talking much much more about data There is much more many many more topics to discuss Make sure you understand these topics and bits and pieces go to far hat lectures and look at MCQ's that deals with This topic to help you understand it before you move on whether you are a CPA candidate CMA candidate see second date or accounting information system Invest in yourself invest in your career. Good luck study hard and of course stay safe