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Services

Data

Management

We build area-specific, cloud-native, and scalable big data infrastructure for analytics, real-time scoring, decision management, and monitoring.

Assessment & Planning

In the data journey, the starting point of any project should be a thorough assessment. To determine the data maturity level, we will conduct studies at all levels with the relevant administrative bodies to examine the data, data platform architecture, and current data pipelines and prepare an assessment document for the project.

Identification of the Processes and Documentation

Data-driven decision-making and putting data and analytics governance at the heart of your business require a corporate culture transformation. Mindberg.ai delivers a Data and Analytics Governance Guideline in light of your company's strategic objectives. This policy document includes the institutional procedures and standards to address tasks for day-to-day data operations excellence.

Data Management

Effective management of Data Management requires various tools, systems, and approaches. Any data management initiative must include the detection and identification of data elements as an essential step. Maintaining high-quality Master Data is crucial for a healthy data lifecycle. Additionally, careful design and documentation of data structures are necessary for Metadata and Data Model Management.

Data Architecture and Data Integration

When choosing the architectural structure for data management, we should evaluate the advantages and risks for each candidate structure and consider the business needs and the company dynamics. In a world where we aggregate data from hundreds of internal and external sources, Mindberg.ai delivers the standards for merging data from different sources, copying it to various systems, or virtualizing it.

Data Quality Management

Data Governance sets the stage and provides the structure for applying Data Quality measures. They work in tandem to ensure that data is a reliable, valuable asset for the organization. At Mindberg.ai, we deliver a data quality framework that introduces measures for accuracy, consistency, singularity, completeness, timeliness, and compatibility of your data assets and flows.