How to create data standards · 1. Define the main business fields · 5. Today's average company has more than 50 customer experience (CX) solutions, 21,000 connections between applications and people, and an annual SaaS revenue of 30%. And even if different data is tracking the same thing, they may not be tracking it in the same way.
Something as simple as saying “24 SNEAKER” instead of “24 sneakers” may seem silly, but it can actually cause significant disruptions for other teams and platforms that want to use, analyze and measure this data. According to the World Wide Web Consortium (W3C), a standard must meet the following requirements to obtain the distinction of “open standard”. The widely-cited supergraphic of the marketing technology landscape sheds light on the scope of the problem from the perspective of Markops, and estimates that there are at least 10,000 active Martech solutions available today. Data standards are necessary to develop the best-in-class technology package, regardless of providers, because there is no single platform that “does it all”.
Finance, human resources and sales technology are experiencing similar growth and are facing the same challenges, which are compounded by their incorrect marketing data. Before creating a new open standard, you must understand the problem that the standard will or need to solve. When considering the problem, it is useful to understand the ecosystem in which the standard will operate. The ecosystem is the people and organizations that produce, use or share data, the relationships between them and the existing data infrastructure.
Data standards are the guidelines by which data is described and recorded. To be able to share, exchange, combine and understand data, we must standardize the format and meaning. A data standard is a type of standard, which is an agreed approach to allowing for a consistent measurement, qualification, or exchange of an object, process, or unit of information. Open data standards are reusable agreements that make it easier for individuals and organizations to publish, access, share and use better quality data.
An open source example is OpenStreetMap (OSM), a collaborative project to create an editable and free world map. Tips on where to share data so that it's easy to find: Organizations that use the International Aid Transparency Index (IATI) add data sets to the data warehouse, which combines all the data published in the standard for easy reference. Data standards are developed by consensus of experts in the field and are ratified by a standardization authority, such as the International Organization for Standardization (ISO) and the Federal Committee for Geographic Data (FGDC). In addition, data standards are often comprised of smaller components, interchangeable parts, or common basic components that can be mixed and combined for different purposes.
Share how up-to-date the data sets are so that data users can determine if the data is useful for their purpose or update their versions; data publishers can provide publication dates as part of a data release using the Open Contracted Data Standard. If you follow these steps, you will reach a more evolved level of data strategy by achieving a common language for all teams, tools and partners. Examples of data standards exist everywhere: global data standards, federal and national data standards, industry data standards, niche-related standards, supply chain data standards, and more. A data standards package is a specification that articulates the implementation of most of the different components of a complete standard data anatomy.
Data is used by a variety of people and organizations, including people and organizations that use data and develop tools and services for research and more. Data coding standards define the rules for structuring and organizing data for use in a given context. Most organizations have a marketing taxonomy, the data language that, ultimately, the brand wants everyone to use. Using Adobe's ubiquitous marketing technology as a use case, this video outlines the role and benefits of data standards as they are applied to marketing departments.