The amount of data created and consumed the world over is growing at a rapid pace. Statista reports that the total amount of data created, captured, copied, and consumed globally reached 64.2 zettabytes in 2020. This means that for organizations to create any value from data and derive meaning, they need to first work on the data in order to publish clean, validated, and accurate data as one source of truth.
If organizations do not have data governance strategies in place, then deriving any value from their data will be difficult. You can expect several data challenges in the data lifecycle process and if you do not have the tools to mitigate those challenges, business intelligence and analytics will be an elusive goal for your organization.
At To-Increase, we have built solutions that help organizations with every stage in their data management journey from data quality management, application integration, master data management, data entry workflow, data preparation, to analytics, and business intelligence. So not only do we understand the need to have data management processes to derive meaning from your data, but we can help you navigate this process with ease every step of the way from data creation to business intelligence.
In this article, we outline the challenges between data creation to publishing data in the data lifecycle and share the capabilities of our solutions which can help you surpass those stumbling blocks. If you are interested in knowing more about challenges post these stages in accessing data quality, deriving value from your data and maintaining a sustainable analytics solution, then read our linked pages.
As part of the data lifecycle, there are a few stages that we highlight below and also share the challenges at each stage
When you create the data and type it or import it, it might not be complete or validated if there are no data governance strategies and tools implemented. So, the challenges faced are:
The next step after the data is created or imported is to check and validate the data. The data stewards need to check if the data is complete and meets all business requirements in the application based on the data governance strategies outlined by the organization. Below are the challenges faced by organizations in this step:
After the first two steps, once the data has been approved it can be published and distributed to the organization. Challenges in this step are:
After a while there might be some request or change, then the data can be updated or imported. And the process begins again with stage 1 of refining the data quality. Challenges faced in this stage are:
During the steps listed above, there are some challenges faced by business users and data stewards. To help them with these challenges we have built some solutions.
We have five solutions that help with step 1. All our solutions are built for Microsoft Dynamics 365.
Using Data Quality Studio, you can validate data for example email addresses or product data. And also set up rules to enforce data quality upon creation, import and legacy data checks by means of configuration and not coding.
For importing the data, you can use the combination of Connectivity Studio and MDM Studio as our solutions offer an easy-to-use, no-code integration setup with configurable mappings.
For fields that need to be accessible or restricted, you can use our Dynamic Field Security solution. The solution allows you to set local or global values or fields for added security depending on the application.
We have three solutions that can help you complete and validate your data.
Our latest addition to the Master Data Management suite is Data Entry Workflow. The solution helps you streamline data entry by setting up steps. And each step can be assigned to different persons who can complete the data with a limited set of fields that are required for them to complete.
During the data entry, we must take into account data quality where at the time of completing and validating data, our Data Quality Studio solution can execute all those rules and Dynamic Field Security can be used to restrict and make certain fields available for the users entering the data.
We have three solutions that can help you with this challenge.
Once the data has been published, it will be live in a master data management company and MDM Studio will ensure all the data can be distributed to local companies and even external applications. There might be an issue where certain data is not complete for local companies for example the text details might not be complete for various disparate applications and then you could use one of our tools such as Data Entry Workflow to complete the data. While rules enforced by Data Quality Studio will ensure that any data entered is validated and accurate.
We have four solutions that can help you with this step.
Our Dynamic Field security and Data Entry Workflow solutions will ensure that when the data needs to be updated, only specific data owners have access to certain fields and data quality rules ensure that the data changed is validated and accurate.
In this blog, we have presented the full data lifecycle and its challenges. At To-Increase, we have built a value chain with our data governance solutions that can play an integral role together or as stand-alone solutions.
While it is important to be proactive rather than reactive to resolve challenges in your data lifecycle, you need to first understand what those challenges are and if our solutions would be the right fit for your organization.
If you think our solutions that are configuration-based, no code solutions built for Microsoft Dynamics 365 fit into your data governance strategy, reach out to our experts. Our experts can understand your data governance strategy and share their recommendations based on your business requirements. In the meanwhile, we also recommend browsing our solution pages and downloading our data governance factsheet.