The most vital part of any Big Data platform is ingesting data at high speeds. It is all about placing the data in the database for either storage purposes, or for analytic uses that will help drive business outcomes. We have prior experience with ingesting large data sets of different formats, whether it be structured, unstructured, real time or batch.
Data Transformation and Quality
Once the data is ingested, it is time for it to be transformed into an analytical friendly format. The better the data is modeled, the more efficient it will be for analytics to provide useful insights that can help drive business decisions. Data transformation can be simple or complex, depending on the type of data that needs to be transformed (i.e. text, xml, csv…) and the cleanliness of the data. Our team has successfully transformed data from different formats and turned it into valuable and useful insights to help clients make business decisions.
Transforming the data comes hand in hand with data quality, which helps ensure the data validates the real-life scenario, meaning it correctly represents the real world construct it refers to.
Proper data governance is often overlooked but is truly the key for any successful data transformation or implementation, as it ensures the standardisation and consistent handling of an organization’s data. We are experienced in providing data platform solutions that have air tight security measures, to ensure no data leaks will occur. We are able to provide full access control, in order to make sure that only authorized personnel can access different parts of the database.
From our experience, we have found that the high availability and disaster recovery is of utmost importance when it comes to databases, as for many companies their data assets are their blood line.
All the data ingestion, transformation and governance that takes place is designed to build a centralized database, typically referred to as an Enterprise Data Hub. This is the key to unlocking all business value from the different data assets. Consolidating the data into one centralized system increases performance and allows for multiple use cases to be explored using the same data. After the data is consolidated, many different users are allowed access to the data in order to find potential links and relations which would help in making important business decisions.