Accelerate your journey to becoming a data-driven organization by defining and implementing the right data management strategy.
The data that drives your operations and fuels the core of your business is growing exponentially, across many applications such as Salesforce, SAP, Endur, Allegro, Openwells, Aries, and internal solutions; all of which are running in disparate locations including cloud-based providers such as Amazon AWS, Microsoft Azure, and Google Cloud. You need a single view of your key entities, across your various data lifecycles and functions, such as Customer (name, location, status), vendors, suppliers, well-header, finance, gross margin & P&L, risk management, logistics, sales, and production, to gain an enterprise perspective of where you stand and where you are headed.
How Sullexis Can Help
Develop Your Data Management Strategy
You need a clear vision, strategy, and roadmap for becoming a data-driven organization. Sullexis can bring its proven Industry experience across Energy (Upstream, Midstream, Downstream), Trading (ETRM Analytics & ML), Logistics, Finance, & Insurance, and our data management methodology to help you create:
- An Information Framework that will support your business’ and data management needs
- A Data Strategy that provides leading practices in establishing the Information Framework
- An Implementation Roadmap identifying the initiatives to implement the Information Framework and includes an initial set of Data management (governance, quality, profiling) accelerators to get started.
Implementation and Data Integration
Once you have defined your data strategy, you need to implement the supporting technology solution and associated process changes to optimize the production & supply chain. Sullexis is experienced with the leading data quality & management platforms, big data solutions, and has deep multi-industry and cross-domain experience in adopting and defining data standards and integrations. Sullexis can help with data quality and management solution selection, design, implementation, and integration:
- Strategy & Planning – focused on providing a business implementation strategy, Infrastructure and Architecture Optimization Strategy, and Execution Roadmap. Use case Example: Enterprise Information Strategy
- Design & Implementation – Sullexis will bring its relevant domain expertise; ability to quickly lay-down the technology foundation needed for enterprise analytics; know-how to create a fully functional set of Operations KPIs; and experience defining a roadmap to implement advanced analytic needs. Use Case Example: Data Lake and Data Analytics for Energy Services
- Integration of People, Process, & Technology – Sullexis will provide a standard governance methodology to help you align people and processes to enable consistency at the corporate/enterprise level while allowing you the flexibility for region/business-specific operational activities. Use Case Example: Information Governance
Sullexis uses an iterative implementation approach that starts with a minimum viable product (MVP) release that allows your organization to see demonstrable and realizable benefits to the end-users from the very first release which builds on one another with each iterative release thereafter.
Assess, Improve and Sustain Your Data Quality
Your existing data has been migrated and integrated into your data management solution, but that data is not perfect and continues to evolve. Robust processes are required to gather, cleanse, conform, reconcile, validate, authorize, and publish the approved master data. These processes need to support ownership of the data by the business, with IT as custodian, at each of the stages throughout the data lifecycle. Sullexis partners with your IT and business teams to define the roles and responsibilities for data ownership and governance. We will train and equip these business teams for their new roles as data stewards.
If you are looking for a way to get started, Sullexis has a quick-starter program that leverages your existing tools as well as native AWS and Azure capabilities to identify your current data quality challenges and quickly implement a data quality processes, systems and dashboards to support continual improvement of data quality in a sustainable fashion.
Over time, transactional system data can become stale containing inaccuracies and duplicates. We have helped numerous organizations clean-up and enhance their data in order to drive operational efficiencies and enable analytics activities.