Data stewardship: An introduction

Catalogue number: 892000062020013

Release date: September 23, 2020

By the end of this video, you should understand how to determine what data you need, where to find data, how to gather data (whether from existing sources or by doing a survey) and how to keep data safe.

Note that data gathering is usually called "data collection" when conducting a survey.

Data journey step
Foundation
Data competency
Data gathering
Audience
Basic
Suggested prerequisites
N/A
Length
8:38
Cost
Free

Watch the video

Data stewardship: An introduction - Transcript

Data stewardship: An introduction - Transcript

(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Data stewardship: An introduction")

Data stewardship: Data governance in action

Data stewardship is often described as data governance in action. This video introduces you to the fundamental aspects of data stewardship.

Learning goals

This video is intended for learners who wish to get a basic understanding of data stewardship. No previous knowledge is required. By the end of this video, you'll be able to answer the following questions: What is data stewardship? What's the difference between data governance and Data Stewardship? Why is data stewardship important? What are the main roles of data stewards and what are the expected outcomes of a data stewardship program?

Steps of a data journey

(Diagram of the Steps of the data journey: Step 1 - Find, gather, protect; Step 2 - explore, clean, describe; Step 3 - analyze, model; Step 4 - tell the story. The data journey is supported by a foundation of stewardship, metadata, standards and quality.)

This diagram is a visual representation of the data journey from collecting the data to cleaning, exploring, describing and understanding the data to analyzing the data, and Lastly to communicating with others the story the data tell. Data governance and actionable data governance in the form of data stewardship principles cover all the steps of the data journey, also called the data lifecycle.

What is data stewardship?

Before discussing data stewardship, it's important to briefly introduce data governance and describe the link between the two. Data governance is often described as the exercise of decision-making, an authority for data related matters. Data governance includes policies, directives, and regulations on data, data privacy and data security, and the assignment of roles and responsibilities to ensure continuous data quality and data management improvement. Data stewardship is often described as data governance in action. Data stewardship includes the management and oversight of data to ensure fitness for use and compliance with policies, directives, and regulations.

What is the difference between data governance and data stewardship? Data governance

Data governance is strategic and involves: creating an organizational structure that's responsible for managing governance decisions, creating a multidisciplinary and coordinated team of stewards to govern the data, defining the uses and purpose of the data and the principles by which they will be handled, establishing a plan to communicate the policies that govern the data, defining the roles and responsibilities for those who oversee data governance.

What is the difference between data governance and data stewardship? Data stewardship

Data stewardship is operational and involves identifying what data are critical and documenting the allowable values of the data. Defining operational procedures to meet the requirements defined by organizational policies regarding the creation, collection, storage, or use of, and denial of access or data. Documenting data sources which involves using a system for recording where data come from. Establishing thresholds or acceptable levels for the quality and usability of the organisations data. Ensuring compliance of data management and interoperability standards that enabled data linkage and allow computer systems to communicate with each other. Adding and managing metadata that describe the data and resolving any issues that arise related to the organisations data.

Why is data stewardship so important?

The rapid increase of data and data providers is often referred to as the data revolution or the data explosion. This increase in volume and variety of data presents many opportunities for organizations to develop more output in the form of data, information and insights. However, there are also growing concerns with data privacy and security. Since some of these data contain identifiable information. With the increase in volume, variety and speed at which data can be created, users expect more data provided in or near real time and at ever increasing levels of detail. There's a growing native many organizations to increase data sharing and data interoperability in order to use data assets to their full potential. Proper data management and stewardship have never been more important.

What is the role of a data steward?

A data steward is accountable for the organisations data assets and must know where the data assets reside throughout their life cycle, what their measure of quality is and how they are protected against associated risks. Data stewards are responsible for defining and implementing policies and procedures for the day-to-day operation and administrative management of systems and data, including the intake, storage, processing, an transmission of data to internal and external systems.

Data steward activities?

The primary roles of data stewards vary between organizations, but most data stewards are directly involved in the following activities. Data lifecycle management from obtaining data to data deletion: This includes protocols, processes and rules for data storage, access, archiving and deletion. Data protection and privacy: This includes ensuring the use of masking or de-identification techniques to protect identifiable information. Data quality: This includes adherence to data quality frameworks to ensure the day to meet the needs of the users. Interoperability standards: This is the use of data standards, vocabularies, taxonomies and ontologies to permit data reuse and sharing. Training: this ensures everyone in the organization understands the role of the data steward. Communication: This includes the creation of reports on the state of data asset management. Policy instrument implementation: This involves ensuring that data adherence to all organizational policies, directives and guidelines throughout their life cycle. Data access management and security: This includes adherence to access privileges and protocols that are based on roles and right to know.

What does data stewardship look like?

When done successfully, data stewardship insurers overall data management is fully aligned with an organisations corporate strategy and supports organizational performance. When done successfully, data stewardship ensures overall data management is fully aligned with an organisations corporate strategy and supports organizational performance. Sound data stewardship also includes also includes repeatable an automated business process is well established roles and accountabilities for those responsible for data, and ensures that business rules are adhered to and that metrics and audits are used to continuously improve data quality and affective data stewardship.

expected outcomes

The expected outcomes of a data stewardship program are: Greater trust in information; Greater understanding of the data needed to make critical business decisions because of accurate terms and definitions; Adherence to best practices, protocols, rules and standards leading to greater efficiency; Consistent results across lines of business, and less time spent finding data, creating reports, verifying results, investigating anomalies and explaining inconsistencies; More consistent, findable, and defendable data and information leading to maintained public trust.

Goals of data stewardship

The goals of data stewardship and a data stewardship program are to: support high quality and optimized data use; Facilitate data discoverability and accessability; Help set common data definitions, standards and policies to support interoperability; Reduce the time spent finding data, verifying results or identifying inconsistencies; Help eliminate duplication in the acquisition and storage of data; Support affective data governance and strategies.

Recap of key points

Data governance is strategic and involves creating an infrastructure for looking after data in a responsible way. Data stewardship is data governance in action. In other words, data stewardship involves the day-to-day activities of gathering, storing, processing and sharing data. Data stewardship is important as we use and are held accountable for the protection of greater volumes of data.

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