Acunor的动态

Opportunity

A Career in Data Governance ?? Data governance is essential for ensuring the accuracy, security, and compliance of health information. Careers in data governance can include roles such as data analysts, privacy officers, compliance specialists, and information security managers. These professionals work to create and enforce policies and procedures that govern the collection, storage, and use of data. They also collaborate with other stakeholders to ensure that data is used ethically and responsibly. ?? If you're interested in a career in data governance, consider gaining experience in areas such as data management, analytics, and compliance. A strong understanding of legal and regulatory requirements is also important. With the right skills and experience, you can make a meaningful contribution to this important field. ?? #DataGovernance #HealthcareCareers #DataAnalytics

Great way to explain key data governance roles and responsibilities Is there anything you see missing ? Thanks for sharing Charlotte Ledoux Let’s discuss in the comments! P.S. Share this post to get more perspectives! ?? #datagovernance #dataroles

As a Data Manager, I would strategically develop and implement data governance policies and standards to optimize data utilization across the organization. My role would ensure that data is not only accessible but also secure, accurate, and efficiently leveraged for maximum impact to drive informed decision-making and ultimately business growth. With optimal data utilization, strategic decision-making becomes seamless, empowering organizations to achieve flawless outcomes. The complexity of the critical players in data governance such as a data manager, as simply put by Charlotte Ledoux below, lies in their leadership definition and strategic intensity and not much on their technical acumen. #DataManagement #DataAnalytics #DataGovernance #DataStrategy

Roles, accountabilities, and responsibilities are the “who and how” that form your Data Governance Framework. You know that you need people to be accountable and responsible for the critical data you identify, but what does that mean? ?? Figuring out what these roles look like and getting stakeholder agreement to take on these roles is the first activity your stakeholders perceive as ‘data governance’. ?? Data Governance Sponsor is usually the most senior person who started the data governance ball rolling. This person needs to be in a credible position to fulfil the role of data governance sponsor, with enough gravitas to influence the most senior stakeholders. ?? Data Governance Leads govern and manage data appropriately, the firm needs to identify and assign specific roles and responsibilities. They provide oversight and support for all data governance to ensure awareness and participation across the firm. They also drive decisions on data standards, definitions, and best practices. ?? Data Owners and Stewards are two of the essential ‘people roles’ for you to define and implement since they will be involved in most of the data governance framework conversations. #IronCarrot #DataGovernance #DataManagement #LawFirmDataGovernance

?? Ownership - A big unresolvable topic in Data Governance Magic but inevitable for an Organization !!! How to identify the Data Owners ? ? Look for individuals or teams whose roles naturally involve the mgmt, oversight and accountability of specific data sets. ?? Find out who has the authority to make key decisions about the data, incl. access control mgmt, usage monitoring and maintainance. ?? Determine who has historically been responsible for the data, incl. its quality, security, and compliance with regulations. ?? Most important - find the individual who has full control over the data but denies ownership when asked ?? #DataGovernance #DataOwners #DataStrategy #DataStewards #DataEngineers #DataDomain #DataManagement #DataQuality #Metadata #DataProduct

Hello, ? Hope you are doing well !!! We are constantly on the lookout for professionals to fulfill the staffing needs of our clients, and we currently have a job opening that may interest you. Job title: Data Engineer Location: Tampa, FL (Onsite from day 1) Position: Fulltime ? Job Description: ? Collaborate with the project team to identify various sources of risk data. Work with data owners and understand its format, structure, and any access restrictions. ? Implement procedures to extract data from various sources. This might involve writing scripts or using data integration tools to automate the data extraction process. ? Cleanse and transform the extracted data to ensure consistency and compatibility with the target risk management system. This may involve handling missing values, formatting inconsistencies, and applying data quality checks. ? Design and implement a data storage solution for the risk management system. This might involve selecting appropriate database technologies or cloud storage solutions based on data volume, performance requirements, and scalability needs. ? Depending on the project's needs, the Data Engineer might be responsible for setting up and managing a data warehouse to store and analyze historical risk data, or a data lake for storing all raw risk data in its original format. ? Implement data security measures to protect sensitive risk data. This includes defining user access controls, encryption strategies, and audit logging to ensure data integrity and compliance with regulations. ? Build automated data pipelines to extract, transform, and load risk data from source systems to the target risk management system. ? Schedule and orchestrate the execution to ensure data is extracted, transformed, and loaded at the desired frequency, inclusive of workflow management tools or scripting techniques. ? Monitor data flow for errors or failures. Implement data quality checks throughout the data ingestion process to ensure the accuracy, completeness, and timeliness of data within the risk management system. ? Collaborate with data analysts and business users to understand their risk data analysis requirements. Translate these requirements into technical specifications for data extraction, transformation, and storage. ? Collaborate with Technical teams to ensure the data engineering tasks align with the overall IT infrastructure and security policies of the firm. You can share your resume at [email protected] or connect with me at +1 312-584-0530. #DataEngineer #Data

?? Data Architect vs. Data Governance Manager: What's the Difference? ?? In the world of data, roles can often overlap and get confusing. Let’s clear it up! ?? Data Architect: Designs and builds data systems and structures. Think of them as the blueprint creators for data management. ??? Data Governance Manager: Ensures data quality, security, and compliance. They are the guardians, making sure data is used correctly and safely. ?? Your turn: How do these roles interact in your organization? Share your experiences, challenges, and insights in the comments! ?? Let’s demystify these crucial roles together and strengthen our data-driven community! #DataArchitecture #DataGovernance #DataRoles #CommunityEngagement #DataManagement

*Data Management and Governance Pills - Data Quality* Once the data is protected, the organization has the necessary condition to take the next step towards managing its data: ensuring that its data is of high quality. According to the DAMA DMBoK? v.2, this is a fundamental point in data management. The data must be reliable. Otherwise, it is not possible to meet the needs of the business, either in day-to-day operations or in decision-making. In order to have quality data, it is necessary to plan and implement data quality management techniques to measure, evaluate and improve its condition so that it can then be used reliably in the organization. To help the Data Quality Analyst in this task, they can make use of (1) a set of tools, be they profiling, identification, data matching, data discovery, among others. Also, (2) it is recommended that they work closely with the main users who consume this data, so that they can extract from them their perception of the degree of quality with which the data is seen in the organization, as well as the characteristics that make the data high quality. Regulatory items such as policies and standards also support their activities. According to the DAMA DMBoK? v.2, the main benefits that an organization can obtain from using high-quality data are: ? Improved customer experience ? Increased productivity ? Risk reduction ? Ability to act on opportunities ? Increased revenue ? Competitive advantage gained from insights into customers, products, processes and opportunities Data quality management is a job that is carried out constantly and at all stages of the data lifecycle (collection, storage, processing, etc.). It also requires planning, commitment and the mindset of incorporating quality into processes and systems. Data Quality supports Data Governance by having a direct impact on the effectiveness, reliability and usefulness of information within an organization, generating accurate, reliable, consistent, complete, current data that contributes to: operational efficiency; compliance and security; decision-making; building and maintaining the organization's reputation (internally and externally). #datagovernance #dataquality #datamanagement #datamanagement #dataqualityreporting #datagovernanceanalyst #dataqualityanalyst #DAMA #DMBoK #datagovernanceprogram #regulators #strategicactive #data #education #collaboratingwithdatagovernance #dataarchitect #databankadministrator #dataengineer #datascientist #monitoring #quality #metrics #policies #standards #audit #organization #consistency #accuracy #reliability #efficiency #efficiency #processes #systems #qualitygrade #datavictorycycle #reliabledata?