MANAGED ANALYTICS
Creating and maintaining an analytics platform
Organizations must overcome data silos, poor data quality and invest in scalable analytics infrastructure to bridge the gap between data generation and actionable insights.
With Affirma you can efficiently manage and maintain your analytics platform.
Data Scientists spend 80% of their time finding, cleaning, and organizing data.
According the Harvard Business Review.
62% of IT professionals reported that repetitive manual processes, cleaning up raw data, and manual data merging and reconciliation are significant challenges in data lakehouse environments. [1]
Ingest metadata of data sources and integrations
Ingest your data models, data schemas, integration schemas, and any applicable industry standards. Cataloging them is the first step in being able to integrate them into your data architecture, for access across multiple technologies and platforms, regardless of your approach to technology architecture.
Build your semantic model
Select relevant data from the Data Catalog library as building blocks for the Enterprise Semantic Model to establish a common understanding of data by defining consistent and clear definitions for all stakeholders to understand and utilize. This is where you start to harmonize data across your data architecture.
Use metadata to design and transform
Create metadata tags and classifications to reflect rules outlined in policies and in regulatory requirements by identifying key components such as compliance needs, data sensitivity, access control and others to guide data handling. Establish metadata values such as internal, public, or confidential for data classification.
Integrate with and generate consuming systems
Build Automation is most effective when the design artifacts are connected to the generated code creating a clear line of sight from the source of the data, through the movement, transformation, storage and finally the usage of data.
Using data to build strategy
DATA-DRIVEN STRATEGY TO BREAK THE TECHNICAL DEBT CYCLE
Percent of value derived in business transformation enabled by technology. [2]
Changing Your Data Management Reality
The reality we face today is an exponential growth of data with the potential to drive operational efficiencies and innovation. But this deluge of data needs to be managed, in a structured way, through processes, frameworks, practices and ideally driven by technology...
Garbage In Is Garbage out – The Importance of Data Labels
There is a common expression in technology domains being “garbage in, garbage out”. The expression was popular in the early days of computing and is even more relevant today as we utilize innovative technologies such as machine learning and artificial intelligence,...
Affirma Product Update – Knowledge Graph Viewer
Visualization helps turn abstract ideas into tangible insights. Whether you are solving complex problems, aligning a team, or setting goals, being able to see something often makes it real and easier to grasp. To foster alignment and smarter decision-making, it's...
