Data Engineering
Is your data out of control?
Common data engineering challenges
Given that data engineering projects are gaining popularity and use cases are becoming increasingly complex, there are challenges that teams may encounter along the way:
Data growth and
storage issues
Difficulty integrating multiple data sources
Lack of support and maintenance for ETL (Extract, Transform, Load) processes
Lack of proper understanding of massive data
Data access and sharing issues
Lack of data governance and management
Unclear
Data Strategy
Performance and Scalability issues
Handling
If your organization lacks a data engineering strategy, the data collected is essentially useless.
DAECO's data engineering service enables you to successfully tackle these challenges
How is our data engineering process?
01 – Ingestion
This is the task of data collection, which depending on the number of data sources, can be focused or large-scale.
02 – Processing
During this phase, ingested data is classified to achieve a specific dataset for analysis. For large datasets, this is commonly done using a distributed computing platform to achieve scalability.
03 – Storage
This phase takes the processing results and stores the data for quick and easy retrieval. The effectiveness of this phase depends on a robust database management system, which can be either on-premises or in the cloud.
04 – Access
Once implemented, the data is available to users with access.
Data engineering is the process of designing and building systems that enable the collection and analysis of ;data from multiple sources and formats
What will you gain from leveraging DAECO's data engineering services?
A comprehensive data
management strategy with a data governance plan.
Align data collection methods and centralize data to a single location.
Maintain and update the data architecture.
Integration of systems across all departments of the organization.
Monitoring and management of all data systems.
Increase business domain knowledge.
Design and develop data architecture based on existing enterprise systems.
Structure and enhance the quality of collected data.
Optimization of data architecture to address anticipated business challenges.
Governance – Management – Security – Scalability – Confidentiality – Support
Unlock the power of big data and harness the benefits of a data-driven approach
Become a data-driven organization and accelerate your digital transformation with enterprise data management for making immediate business decisions.
