We structure your data
Through a thorough audit of your data sources, we centralize and structure your information schema. This approach speeds up the processing and analysis of your company’s data over the long term.
We help you create a single center of truth that can be connected to all your data sources and easily digested by analysts or visualization tools.
Why structure your data?
Centralized data prevents duplication and inconsistencies.
Data is more easily consumed by third parties such as tools or analysts.
A robust, flexible structure makes it easy to add new data sources in the future.
The stages of a data strategy
Your data strategy depends above all on your current information structures and your organization’s objectives. A good strategy must combine a tangible vision with a robust and flexible technological approach.
It all starts with a rigorous census of the company’s data. This includes the analysis of all digital and physical documents, enterprise software and existing data warehouses.
Based on the data collected, we identify problems of duplication, inconsistency and standardization in the current structure. We then propose a centralized schema that guarantees data integrity despite the aggregation of multiple sources. Finally, we draw up a technical plan for migrating your information to the new schema.
Once the technical plan has been drawn up, our team designs the migration, cleansing and unification scripts needed to implement your new data schema. We select the technology best suited to your volume of information, and configure a high-performance infrastructure to host your data securely.
What our clients say
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The Trajectory Explorer is an online tool designed to facilitate the comparison of possible transformation paths to achieve zero net GHG emissions in Canada by 2050.
Matchwork is a B2B and SaaS platform for human services agencies supporting individuals who face barriers to employment.
Increasingly widespread, electric car-sharing in municipalities is as much an organizational challenge as a technological one. The SAUVéR platform facilitates fleet management, car-sharing and equipment sharing on a municipal and regional scale, from dispatching to invoicing, via control systems.
A data strategy helps guide and structure your company’s efforts to collect, analyze, store and use data. It ensures that your data is used optimally to support your business objectives, improve decision-making, drive innovation and maintain a competitive edge. Without a clear data strategy, your data management efforts could be inconsistent, inefficient and at risk of failing to comply with privacy and data protection laws.
An effective data strategy includes several key elements: clear objectives aligned with your business goals, an understanding of the availability and quality of existing data, guidelines on data collection and management, planning for the technological infrastructure needed to store and analyze data, measures to ensure data security and confidentiality, and a plan for training and developing the skills needed within your team to work with data.
Data strategy must be closely integrated with your overall business strategy. The objectives of your data strategy should directly support your business goals. For example, if your business objective is to improve customer service, your data strategy could include collecting and analyzing data on customer behavior and preferences to improve the customer experience.
It’s crucial to integrate legal and ethical considerations from the outset of creating your data strategy. This can include seeking legal advice to understand applicable laws and regulations, putting in place policies and procedures to ensure data consent, confidentiality and security, and putting in place monitoring and auditing mechanisms to ensure ongoing compliance with these policies
The time needed to develop a data strategy can vary considerably, depending on the size of your company, the complexity of your operations and your specific objectives. It can range from a few weeks to several months. It’s important to note that developing a data strategy is an evolutionary process that needs to be reviewed and updated regularly to remain relevant and effective.