Data Transformation and Validation Solutions are the activities needed to structure data into a format that is suitable to be used by the sender or receiver of the data, and to ensure that any data that is sent or received is validated against a set of requirements to ensure its proper context. The data is initially provided in its source state and then transformed into its destination state. The source state of the data may be unstructured or it may be structured data – containing a defined context. In either case, it is necessary to identify the transformation requirements in order to achieve the desired destination state of the data.

Data transformation requires capturing all of the necessary data context, data content, and transformation rules necessary to properly structure and present the data as anticipated. The quality of data transformations is dependent upon clear transformation specifications. Without them, your data transformations are at risk, which can provide a cascading domino effect on the quality of information passing through your systems.

StoneDonut utilizes tools within their Xecute delivery framework to properly capture transformation requirements to ensure that the quality and reliability of your information remains intact. Please contact us for more information on our Data Transformation Solutions.

Data Migration Solutions are the activities needed to move large amounts of data from one system to another. Businesses that upgrade their ERP systems, 3^rd party support systems, or custom applications will at one time or another be faced with the challenge of migrating large amounts of data from one system to another. These migrations can be focused primarily on master data – Customers, Vendors, Inventory, etc., but they may also include transactional data as well – open sales orders, purchase orders, GL transactions, etc.

The level of data migration can vary as well –a full data migration where all data is migrated, a partial migration where key data is migrated, or a staged migration, where full or partial data is migrated over time. In any situation, it is important to identify all of the requirements necessary in order to successfully implement a proper data migration.

In many cases, large volumes of data will be involved in this exercise, so the solutions architecture must be capable of handling the requirements of the migration processes. Business expectations must be met, which will involve timing, validation, and verification of proper data migrations. Data Migration may require the implementation of other data management services activities such as data transformation, data cleansing and enrichment, and data synchronization depending upon the data migration requirements.

StoneDonut has successfully deployed data migration solutions – supporting full, partial, and staged migration models across multiple business channels and company sizes. Please contact us for more information on our Data Migration Solutions.

Data Warehouse solutions are the activities needed to establish a central repository of data collected from multiple business systems and other sources inside and outside of the enterprise. These sources may arrive in nightly batches of data, periodic data, or in near real-time transactional data. The data warehouse contains current and historical data, which is then used to create a wide variety of reports for business users throughout the enterprise.

Data Warehouse solutions often require the implementation of other data management services activities such as data transformation and data cleansing and enrichment. Most data warehouse solutions implement a series of environments to stage, warehouse, and arrange the data for use by the business. Data Warehouse solutions are complex and require a great deal of planning in order to create a warehouse environment that provides quality information to its user community within the timeframes expected.

StoneDonut has successfully deployed data warehouse solutions – supporting various data warehousing models across multiple business channels and company sizes. Please contact us for more information on our Data Warehousing Solutions.

Business Intelligence solutions are the activities needed to help business leaders, managers and other business end users make informed business decisions using a wide variety of tools, applications and processes. BI provides businesses with the ability to extract data from reliable sources, prepare it for analysis, develop and run queries against the data, and then create reports, dashboards or data visualizations – providing the analytical results available to business decision-makers, as well as other operational workers throughout the business enterprise.

BI solutions often involve the utilization of tools like Power BI, Tableau, Sisense, Salesforce, etc. They access data stored in data marts or other preconfigured and structured data sources and are used in conjunction with data warehousing solutions. BI resources require an understanding of both the organization of the data as well as its use in the business in order to properly convey the information to the business user community.

StoneDonut has successfully deployed business intelligence solutions – supporting various data warehousing models across multiple business channels and company sizes. Please contact us for more information on our Business Intelligence Solutions.

Data Synchronization solutions are the activities needed to insure that common data persisted in multiple business systems remains identical. Today’s businesses implement many different applications and 3^rd party products – many of these products contain similar data across a wide range of platforms and technologies. These systems can wreak havoc on business systems that are integrated together if common data is not synchronized between them.

Master data management is one of the primary challenges with duplicate data in various systems. MDM tools are often difficult and expensive to implement and maintain due to the agility of the business. Rarely do businesses receive a return on their investment. Rather than attempting such a monumental task, businesses opt for selective data synchronization – addressing specific data synchronization needs that will provide benefit to the business for a period of time.

An example of selective data synchronization would be when a business installs a new ERP system in phases. This requires the old ERP system and the new ERP system to function simultaneously. Data synchronization is then provided to select areas of the ERP systems in order to keep the information in the two systems functioning properly. Each phase of the ERP implementation may require different data synchronization requirements.

Data synchronization is a challenging practice that requires the proper knowledge and skillset to implement. StoneDonut has successfully implemented data synchronization solutions for our clients using a wide variety of technologies. Please contact us for more information on our Data Synchronization Solutions.

Data Cleansing and Enrichment solutions are the activities needed to “scrub” or “enhance” data in order to make it useful information for the business.

Data cleansing is the practice of “scrubbing” data of any unwanted content, so it conforms to the requirements of the business. An example of data cleansing would be the removal of unwanted characters that exist at the beginning or end of the actual data element.

Data Enrichment is the practice of “enhancing” the content of data, so that it conforms to the requirements of the business. Examples of data enrichment would be adding a prefix or suffix the data element. Data enrichment can also involve more complex processes such as accessing an external system in order to determine the format of the data.

StoneDonut utilizes tools within their Xecute delivery framework to properly capture data cleaning and enrichment requirements to ensure that the quality and reliability of your information remains intact. Please contact us for more information about our Data Cleansing and Enrichment Solutions.