SMBH Consulting.

Data Assessment: Evaluate your current data environment, including infrastructure, governance, and quality, to identify opportunities for improvement.

Data Strategy Development: Create a strategic plan that aligns with your business objectives, including data management, analytics, and technology roadmaps.

Technology Selection: Advise on selecting the right data technologies and tools that fit your needs, including data warehousing, visualization, and analytics platforms.

Data Governance: Develop and implement data governance frameworks to ensure data quality, consistency, and compliance with regulatory requirements.

Data Integration: Integrate data from various sources into a unified system, facilitating seamless access and analysis across platforms.

Data Migration: Manage the migration of data between systems, ensuring data integrity and minimal disruption to business operations.

Data Profiling: Analyze data quality to identify issues such as inaccuracies, inconsistencies, and duplicates.

Data Cleansing: Perform data cleansing activities to rectify errors, standardize formats, and improve overall data quality.

Data Enrichment: Enhance your data by adding external information, improving its completeness and value for analysis.

Descriptive Analytics: Provide insights into past performance through data aggregation and visualization, helping you understand historical trends and patterns.

Predictive Analytics: Utilize statistical models and machine learning algorithms to forecast future trends and behaviors, supporting proactive decision-making.

Prescriptive Analytics: Offer recommendations for optimizing business processes and strategies based on data-driven insights.

BI Strategy: Develop a business intelligence strategy to align data reporting and analysis with your strategic goals.

Dashboard and Reporting: Design and implement interactive dashboards and reports that provide real-time insights and facilitate data-driven decisions.

Self-Service BI: Implement self-service BI tools that empower users to explore data and create reports independently.

Machine Learning: Develop and deploy machine learning models to solve complex business problems, including classification, clustering, and anomaly detection.

Natural Language Processing (NLP): Implement NLP techniques for text analysis, sentiment analysis, and chatbot development.

Computer Vision: Apply computer vision technologies for image recognition, object detection, and video analysis.

Data Protection: Implement robust data security measures to safeguard your data from breaches and unauthorized access.

Compliance: Ensure compliance with data privacy regulations such as GDPR, CCPA, and HIPAA, including data handling, storage, and reporting practices.

Incident Response: Provide support for data security incidents, including risk assessment, containment, and remediation.

Custom Visualizations: Create customized data visualizations to represent complex data in an accessible and insightful manner.

Interactive Reports: Develop interactive reports that allow users to drill down into data and explore various dimensions and metrics.

Storytelling: Utilize data storytelling techniques to present data insights in a compelling and understandable way for stakeholders.

Data Architecture Design: Design scalable and efficient data architectures that support your data management and analytics needs.

Cloud Data Solutions: Implement cloud-based data solutions for storage, processing, and analytics, optimizing cost and scalability.

Data Warehouse Solutions: Develop and maintain data warehouses to centralize and organize data for efficient querying and reporting.