Data Architecture & Strategy Consulting
In today’s data-driven environment, Dataskills supports companies in designing, leveraging, and governing their information assets, providing a comprehensive consulting service on data architecture and strategy.
The engagement focuses on four key areas:
- Data Strategy: We help companies define a data strategy aligned with business objectives, enabling innovation and growth initiatives through the intelligent use of data.
- Data Architecture (Data Warehouse & Lakehouse): We design and implement modern, scalable architectures based on data lakes and data warehouses (including parallel data warehouse environments), supporting comparisons between approaches, such as data lake vs. data warehouse, and enabling AI data analytics, machine learning, and advanced analytics projects.
- Data Governance: We support the adoption of robust, tailored data governance practices to ensure data quality, security, traceability, and regulatory compliance.
- Data Monetization: We make data accessible and actionable for all business functions, from operational reporting to predictive analytics, with customized solutions that maximize return on investment (ROI) and support data analytics and decision automation initiatives.
What does it mean to be data-driven?
In an increasingly complex competitive landscape, the ability to collect, organize, and leverage large volumes of heterogeneous data is a key enabler for innovation and business growth.
Being a data-driven organization means adopting a data strategy aligned with business objectives, building a modern information architecture (based on data warehouses and data lakehouses), and implementing data governance processes to ensure information reliability, quality, and security.
Through these levers, data becomes a tangible asset capable of powering decision-making processes, intelligent automation, predictive models, and strategic insights that go beyond what is achievable with traditional approaches.
Application Areas of Data Architecture & Strategy
Banking & Financial Services
- Predictive modeling for risk assessment
- Fraud detection
- Customer behavior analysis
- Data integration and consolidation of heterogeneous sources
- AI for document management
Marketing e CRM
- Personalized recommendations based on AI models
- Advanced customer segmentation
- Sentiment analysis
- Churn and customer lifetime value analysis
IT & Digital Platforms
- Data integration and migration across systems
- Metadata management and information catalogs
- Data quality and de-duplication
- Real-time data streaming and analysis
Retail & eCommerce
- Inventory optimization and pricing policies
- Sales forecasting and data-driven promotions
- Social and customer feedback analysis
- Integrated supply chain management
Industrial and Manufacturing
- Predictive maintenance on assets and equipment
- Quality monitoring and process control
- Resource tracking and management
- Industrial data visualization for decision-making
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