Focus is usually Only on Management. We are where Data meets Management
Data Management Solutions
Data Strategy Development
A robust data strategy is essential for organizations aiming to leverage their data assets for informed decision-making, operational efficiency, and competitive advantage. This strategy involves a seamless process that ensures data is collected, processed, and stored efficiently, ready to be utilized for various business needs.
We actively work with our clients to enhance their long-term data strategies.
Data Analysis & Interpretation
We use advanced methodologies including statistical techniques and querying languages extracts to collect, cleanse and profile data from various client sources. We also utilize external market intelligence to enhance the information base of our clients.
- Data Collection
- Data Profiling
- Data Cleansing
- Evaluation of Data driven initiatives
Data Governance
We help companies establish/enhance a robust data governance framework that ensures enforcement of policies, standards and controls for data usage, data quality, master data management, security and compliance providing context for responsible and effective data management policies.
- Policies & Standards
- Data Quality Management
- Reference & Master Data
- Issue Management
BI Solutions & Data Visualization
Our BI dashboards allow data driven decision making and an opportunity towards reengineering any inefficient processes, cutting down on cost and spotting new business opportunities.
- Dashboards
- Insights
- Cloud Services
AI Strategy & Implementation
Our AI solutions offer efficiency and seamlessly integrate data, algorithms, and infrastructure thereby empowering organizations to make informed decisions, enhance efficiency, and stay competitive in the rapidly evolving technological landscape.
- Predictive Analytics
- Integrate AI Solutions into Analytics
- Access and Visualize a Growing Library of AI Models
Staff Augmentation
We provide staffing solutions for a wide array of data-driven initiatives, where businesses can tap into a pool of highly skilled individuals, without breaking the bank.
FAQs
Data management is the practice of collecting, storing, organizing, and maintaining data in a way that’s secure, accessible, and usable. Effective data management ensures data quality, consistency, and accessibility for business use.
Data management is crucial for businesses as it enables them to make informed decisions, improve operational efficiency, and gain a competitive edge. By effectively managing data, businesses can uncover valuable insights, optimize processes, and enhance customer experiences. It ensures data accuracy, security, and accessibility, fostering trust and enabling data-driven innovation.
Data management encompasses all aspects of handling data, from collection and storage to analysis and reporting. Master data management (MDM) is a subset of data management that specifically focuses on maintaining a single, consistent view of critical business entities like customers, products, and employees. MDM ensures that this master data is accurate, complete, and accessible across the entire organization, improving decision-making and operational efficiency.
While data management and data governance are often used interchangeably, they have distinct roles. Data governance defines the overarching policies, standards, and procedures that govern data within an organization. It focuses on who owns the data, how it should be used, and how its quality and security are ensured. Data management, on the other hand, is the practical implementation of these policies. It involves the technical aspects of handling data, such as storage, retrieval, and analysis. Essentially, data governance sets the rules, and data management follows them.
Common data management tools include databases (e.g., MySQL, Oracle), ETL tools (e.g., Talend, Informatica), and data cataloging tools (e.g., Alation). These tools help with data storage, processing, and organization.
Data quality refers to the accuracy, completeness, consistency, and timeliness of data. It’s crucial for businesses as it ensures that data is reliable and fit for its intended purpose. To maintain data quality, organizations should implement data profiling, cleansing, validation, standardization, and monitoring processes. By prioritizing data quality, businesses can make informed decisions, improve operational efficiency, and gain a competitive edge.
Data management plays a crucial role in regulatory compliance by ensuring that organizations can effectively collect, store, and manage data in accordance with relevant laws and regulations. For instance, in the healthcare industry, HIPAA mandates specific data privacy and security standards. By implementing robust data management practices, healthcare organizations can securely store patient information, control access to sensitive data, and promptly respond to data breaches. This not only protects patient privacy but also helps the organization avoid hefty fines and legal repercussions.
A data warehouse is a centralized repository where data from different sources is stored and optimized for reporting and analysis. It enables businesses to consolidate and analyze large volumes of data efficiently.
Start by defining data management goals, such as improving data quality or enhancing security. Identify your data sources, establish data standards, and consider implementing a tool to streamline your data management efforts.