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Data Lakes

Data Lake Metadata Management

A data lake requires the storage of vast amounts of metadata. Collected data, such as business descriptions, performance logs, and audit information, comes from different sources at different speeds, making it difficult to combine and manage efficiently.
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How to effectively manage metadata within data lake?

At C&F, we are often approached by clients who are initially struggling with scattered, siloed metadata. When we build data lake platforms for them, we ensure that they have a well-organized, insightful, and agile data asset. We do this by providing a central repository and powerful tools for metadata discovery, lineage tracking, and governance. Our data lake solutions automatically catalog metadata from disparate sources-including databases, files, streaming platforms, and more-to provide a holistic view of our customers' data landscape. We then ensure that the collected metadata can provide a data lineage that visualizes data flows and dependencies, ensuring data integrity and compliance at every step. By listening to our customers, we ensure compliance with regulatory requirements and internal policies with robust metadata governance capabilities.

Single location for metadata

By storing metadata in a single data location, customers benefit from improved reporting capabilities.

Better understanding and confidence in data lake

Collected and combined metadata enables lineage tracking of data dependencies and provides confidence through data load and freshness metrics.

Simplified and automated metadata collection

Automated metadata management allows data lakes to stay current and update key metrics without the need for manual and tedious data collection processes.

Meet compliance restrictions

Adhere to regulatory and compliance requirements regarding metadata management when applicable

As data lakes grow in size and variety of data sources, it is critical to manage their metadata efficiently. Establishing and maintaining a single metadata catalog can bring many benefits to data lake teams by improving data trust and visibility. At C&F, we look at the latest trends in metadata management and select the tools that best fit the project. This includes examining existing metadata catalog tools, identifying bottlenecks, and designing a solution that best fits the existing metadata landscape while addressing the need for expansion.

Overview

Modern data architectures rely on data lakes to store large volumes of raw data that can be harnessed by data scientists for insights, data analysis, and decision-making. Within this, metadata holds important information about the origins, structure, relationships, and usage of stored data. Without effective metadata management, the data stored in a data lake can be scattered, siloed, and unhelpful for data analytics. Our Metadata Management Solutions focus on providing a well-organized repository for data discovery, lineage tracking, and data governance. With automated metadata management, you can improve reporting, ensure data quality, keep data lakes current, and adhere to regulatory and compliance requirements.

Experts in the field

Michał Majkowski
Principal Software Architect
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