Improving Data Efficacy
What is Data Operations Management?
Managing data is at the core of everything that we do at Tibil. We realize that for most of our customers while data operations is not their core business, it is nevertheless critical for the analysis needed for accurate predictions and making their business grow. Improved data management leads to better quality of available data, which results in better analysis. That single source of truth translates into better insights, business strategies and higher profitability.
Common Data Management Platform Challenges
While working on data operations for our customers here are some of the common data challenges we encountered:
- Multiple disparate data sources with no single source of truth
- Large amount of incorrect or missing data
- Hidden costs of data growth – also the data is not easily scalable
- Inaccessibility of data – the data is on multiple systems that are not accessible
- Buried and messy data that’s not easily available for analysis
- Duplication of effort in data creation and extraction
Benefits of Data Operations Management
In Tibil’s view, DataOps is a critical data related activity that is much ignored in many organizations that are generating large amounts of data. We believe that by focusing on improving DataOps, our customers can benefit with:
- Rapid Time-to-Value: Application framework to cut down development speed for each model
- Robustness: Audit framework to increase trust for accelerated & simplified compliance
- Scale & Performance: Scalable models with new use cases and new data
- Managed Evolution: Rapid iterations on the features and model development
- Dynamic Data Platform: Eliminate data friction, accelerate innovation and secure data
- Data Privacy and Security: Continuously deliver data without the risk
Besides Data Operations, we have expertise in Data Engineering solution to help you prepare and normalize data and build data lakes, Feature Engineering solution to help transform the prepared data into derived variables and formats for data analytics algorithms and models, Data Analytics solution to analyse data using statistical models to generate dashboards and reports, Data Science solution to build advanced analytical solutions based on ML algorithms and AI models, and Data Maturity Assessment to help you baseline your current data posture.