Data Architects are most often the stewards of data within the enterprise. They must understand all aspects of the data and how it flows through its lifecycle in order to successfully design and govern their architecture. This includes understanding where their information comes from (a “source”), how it is transformed by business processes, where it resides for use, what data quality issues may exist, how long it can be retained before being archived or deleted, who has access to it and when they need access; and more. To perform this role effectively, an enterprise needs a complete picture of its data assets and how they interact with each other over time.
Data Architecture is the foundation for data governance
Data Architecture is the foundation for data governance. Data Governance is the process of setting standards and controls that help organizations manage their data resources in order to meet business requirements, protect against corruption, preserve confidentiality and ensure availability.
Data Architecture is the foundation for data quality. Data quality refers to the quality of information in an organization’s possession or control, regardless of its source or method of capture (e.g., manual versus electronic). By applying measures of accuracy, completeness, consistency and purity across all types and forms of business information throughout its lifecycle from creation through maintenance to destruction – we can improve overall productivity while reducing risk by eliminating errors from our decision making processes where possible – thereby increasing shareholder value!
Data Architecture is also a key component for security architecture because it identifies what information should be protected based on how critical it is within your organization’s goals/objectives—and then takes steps toward securing those assets using appropriate technologies such as encryption keys management systems and the like.
Why Enterprise Data Architects Need Data Lineage
Data lineage is the most important tool for data architects because it helps them identify and resolve data quality issues. It also provides a visual representation of how information flows throughout an organization, enabling them to gain a better understanding of their business’s data assets.
An enterprise-class solution for managing lineages can be used by both individuals and teams, providing an easy way to manage dependencies between different types of objects (e.g., entities) that exist within one or multiple databases. In addition, this type of platform will allow you to visualize relationships between your systems over time so as not just look at what happens today but also how things were in the past.
Data Lineage provides data architects with a complete picture of the enterprise’s data assets
Data lineage provides data architects with a complete picture of the enterprise’s data assets. It gives context to their work and helps them troubleshoot and remediate issues, as well as prospectively design for compliance and risk management. A comprehensive view of your organization’s data will help you understand:
Which datasets are connected to each other
The lineage of these connections (the relationship between people, systems, or applications)
Who owns which datasets
Data Lineage provides context that enables more informed decisions
Data lineage is a crucial part of the data architecture process. It provides context that enables your data architects to make better decisions and make more informed decisions. With this context, you can ensure that you’re using your data responsibly and making the best use of it with every decision made by your team or organization.
Data Lineage helps data architects to troubleshoot and remediate data quality issues
Data lineage is a key component of data quality management. It helps data architects to troubleshoot and remediate data quality issues, by providing a complete picture of the data assets and the flow of information throughout an organization.
Without a lineage diagram, it’s impossible to know where the data came from or how it was used. This makes it difficult to determine which data sources are most accurate and which might need additional verification.
A lineage diagram shows how data moves from one repository or data store to another. It can also show where data was transformed during the transfer process—for example, when it was converted from a text file into a database record. It’s important to note that lineage isn’t just about where data came from; it also helps determine who is responsible for its quality and accuracy.
Data Lineage allows data architects to prospectively design for compliance and risk management
Data Lineage is an essential tool for enterprise data architects. Data Lineage allows data architects to see the complete picture of the enterprise’s data assets, providing them with context for making informed decisions about how best to remediate issues and deliver value back to business stakeholders.
Data lineage can be traced directly back to a single source system or database, through multiple transformations and enrichment activities, until it reaches a final destination system or database. This “chain of custody” provides valuable insight into where your data comes from, what modifications have been made along the way, and who has access to it at each stage in its lifecycle – all while maintaining strict accountability around who creates/modifies/updates/deletes that information over time!
Data lineage can be used to answer a variety of questions, including: – What are the sources and distribution of our data? – How do we track changes to our data over time? – Where is that data located at any given point in time?
Whether you are a new or seasoned Data Architect, make yourself an expert in understanding the flow of information throughout the organization.
Whether you are a new or seasoned Data Architect, make yourself an expert in understanding the flow of information throughout the organization. You should know the data lineage of your data assets and their history. You should understand how your data assets are used and by whom they are used. Lastly, it is important that you understand what they are used for and with.
When developing an understanding of these concepts, it is useful to have a starting point as well as a goal for each piece of work that you do in your role as a Data Architect. For example if there is already structure in place around how analytics teams interact with IT services then perhaps there is also structure around how IT infrastructure interacts with other departments such as sales/marketing?
Data Lineage is a critical tool for data architects. It will help you understand how your data assets flow through the organization, provide context that enables more informed decisions, and enable you to troubleshoot and remediate data quality issues. If you are a new or seasoned Data Architect, make yourself an expert in understanding the flow of information throughout the organization.
Alex Solutions provides fully automated data lineage and auditing services across your entire enterprise architecture. Our Data Lineage products are engineered to deliver the richest level of information available on the market today, delivering meaningful insights into all aspects of your data flows. Alex Data Lineage is cross-platform and cross-application, visualizing every detail of your enterprise architecture. Fully automated out-of-the-box, Alex Data Lineage provides real-time impact analysis and change management capabilities to enterprise Data Architects. These rapid views enable Architects to reduce risk and make trusted changes to enterprise architecture. Alex Data Lineage is so accurate that some of the world’s largest banks use it directly when reporting data flows to regulators. You can learn more about Alex Data Lineage here.
Reach out to us today for a tailored discussion around how Alex Data Lineage can empower your enterprise Data Architecture team: