With over 15 Years of experience in the Oil and Gas industry serving customers across upstream, midstream and downstream, and across Industry sectors, we use Data Science to help organizations to understand what happened, what could happen, and what should happen?

CASE STUDIES

SENSOR DATA

ACCRUALS AND ALLOCATIONS

ACCRUALS AND ALLOCATIONS

Efficiently capture millions of records from ELD devices, Inventory tanks, fuel sales in a scalable computation intensive platform

ACCRUALS AND ALLOCATIONS

ACCRUALS AND ALLOCATIONS

ACCRUALS AND ALLOCATIONS

Manage and Track accruals and allocation of expenses and receivables at a transaction level for analysis, reporting and decision support.

INDEX DATA

ACCRUALS AND ALLOCATIONS

DESCRIPTIVE (WHAT HAPPENED)

Manage stream of data like OPIS pricing, fuel price indexes that are changing frequently using a streaming and messaging platform.

DESCRIPTIVE (WHAT HAPPENED)

PRESCRIPTIVE (WHAT SHOULD ?)

DESCRIPTIVE (WHAT HAPPENED)

Understand and get detailed insights on fuel inventory, pipeline movement through dashboards and metrics.

PREDICTIVE (WHAT COULD?)

PRESCRIPTIVE (WHAT SHOULD ?)

PRESCRIPTIVE (WHAT SHOULD ?)

Predict fuel run-out, contract compliance deviation, device communication failures and forecast demand.

PRESCRIPTIVE (WHAT SHOULD ?)

PRESCRIPTIVE (WHAT SHOULD ?)

PRESCRIPTIVE (WHAT SHOULD ?)

Identify and recommend optimization strategies like where to increase drivers, equipment and management of schedule.

SERVICES AROUND DATA SCIENCE

The concept of applying data engineering principles to  create a data platform is key to establishing a successful data science practice. The wide array of data sources would include transaction data, sensors, IOT, logs and data streams/feeds. The exploration and transformation of datasets are handled using platform specific data pipelines. The datasets are further enriched to have a semantic model for efficient analysis in a structured format.

Business intelligence-drive business intelligence reporting through self-service methods with an effective data governance. Metrics, performance and overview through drill-down dashboards. Advanced visualization techniques for better interpretation

Advanced analytics - descriptive analytics drills down into data to uncover details such as the frequency of events, the cost of operations and the root cause of failures. Predictive analytics provides answers that move beyond using historical data as the principal basis for decisions. Prescriptive analytics provides recommendation for better outcomes.