Value of Data

Organizations are busy with large-scale digital transformation projects to modernize their business processes and improve decision-making and extract value from their operating data. Consequently, the data needs started to grow exponentially. Thus, the client’s next strategic objective is to enable real-time analytics of fast-moving streaming data coming from a large number of different ecosystem (Velocity, Variety and Volume). Additional the lately developments in innovations in Big Data, AI, Data Science, ML and modern data platforms increased Organizations needs to have skilled data engineers to support business initiatives.
Provide subject matter expertise, Avilius Consultants can integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building analytics solutions.
Help project stakeholders to understand the data through exploration, and Avilius Data Engineers can build and maintain secure and compliant data processing pipelines by using different tools and techniques.
Build data pipelines and data stores, that are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints.
Avilius Data engineers can deal with unanticipated issues swiftly, and they can minimize data loss.
Design, implement, monitor, and optimize data platforms to meet the data pipelines needs.

Design a data storage structure

Here are some activities that Avilius Data Engineers can provide to your organizations with regards to design data storage structure.
1 . Design a Data Lake solution in AWS, Azure, GCP and IBM cloud.
2. Recommend file types for storage.
3. Recommend file types for analytical queries
4. Design for efficient querying
5. Design for data pruning
6. Design a folder structure that represents the levels of data transformation
7. Design a distribution strategy
8. Design a data archiving solution

Design a partition strategy

Below are some activities that Avilius Data Engineers can provide to your organizations with regards to design partition strategy.
1. Design a partition strategy for files
2. Design a partition strategy for analytical workloads
3. Design a partition strategy for efficiency / performance
4. Design a partition strategy for Azure Synapse Analytics, Redshift and BigQuery.
5. identify when partitioning is needed in Azure Data Lake Storage Gen2.

Design and Implement the serving layer

Below are some activities that Avilius Data Engineers can provide to your organizations with regards to design serving layer.
1. Design star schemas
2. Design slowly changing dimensions
3. Design a dimensional hierarchy
4. Design a solution for temporal data
5. Design for incremental loading
6. Design analytical stores
7. Design metastores in Azure Synapse Analytics and Azure Databricks.
8. Deliver data in a relational star schema.
9. Deliver data in Parquet files.
10. Maintain metadata
11. Implement a dimensional hierarchy

Implement physical data storage structures

Below are some activities that Avilius Data Engineers can provide to your organization with regards to implement physical data storage structures.
1. Implement compression
2. Implement partitioning
3. Implement sharding
4. Implement different table geometries.
5. implement data redundancy
6. Implement distributions
7. Implement data archiving

Implement logical data structures

Below are some activities that Avilius Data Engineers can provide to your organization with regards to implement logical data structures.
1. Build a temporal data solution
2. Build a slowly changing dimension
3. Build a logical folder structure
4. Build external tables
5. implement file and folder structures for efficient querying and data pruning.

Ingest and transform data

Below are some activities that Avilius Data Engineers can provide to your organization with regards to ingest and transform data.
1. Transform data by using Apache Spark
2. Transform data by using Transact-SQL
3. Transform data by using Data Factory
4. Transform data by using Azure Synapse Pipelines
5. Transform data by using Stream Analytics
6. Cleanse data
7. Split data
8. Shred JSON
9. Encode and decode data
10. Configure error handling for the transformation
11. Normalize and denormalize values
12. Transform data by using Scala
13. Perform data exploratory analysis

Design and develop a batch processing solution

Below are some activities that Avilius Data Engineers can provide to your organization with regards to design and develop a batch processing solution.
1. Create data pipelines
2. Design and implement incremental data loads
3. Design and develop slowly changing dimensions
4. Handle security and compliance requirements
5. Scale resources
6. Configure the batch size
7. Design and create tests for data pipelines
8. Integrate Jupyter/IPython notebooks into a data pipeline
9. Handle duplicate data
10. Handle missing data
11. Handle late-arriving data
12. Upsert data
13. Regress to a previous state
14. Design and configure exception handling
15. Configure batch retention
16. Design a batch processing solution
17. Debug Spark jobs.

Design and develop a stream processing solution

Below are some activities that Avilius Data Engineers can provide to your organization with regards to design and develop a stream processing solution.
1. Process data by using Spark structured streaming
2. Monitor for performance and functional regressions
3. Design and create windowed aggregates
4. Handle schema drift
5. Process time series data
6. Process across partitions
7. Process within one partition
8. Configure checkpoints/watermarking during processing
9. Scale resources
10. Design and create tests for data pipelines
11. Optimize pipelines for analytical or transactional purposes
12. Handle interruptions
13. Design and configure exception handling
14. Upsert data
15. Replay archived stream data
16. Design a stream processing solution

Design and Implement Data Security

Below are some activities that Avilius Data Engineers can provide to your organization with regards to design and implement data security solutions
1. Design data encryption for data at rest and in transit
2. Design a data auditing strategy
3. Design a data masking strategy
4. Design for data privacy
5. Design a data retention policy
6. Design to purge data based on business requirements
7. Design role-based access control (RBAC) and POSIX-like Access Control List (ACL) for Data Lake Storage
8. Design row-level and column-level security
9. Implement data masking
10. Encrypt data at rest and in motion
11. Implement row-level and column-level security
12. Implement Azure RBAC
13. Implement POSIX-like ACLs for Data Lake Storage Gen2
14. Implement a data retention policy
15. Implement a data auditing strategy
16. Manage identities, keys, and secrets across different data platform technologies
17. Implement secure endpoints (private and public)
18. Implement resource tokens in Azure Databricks
19. Load a Dataframe with sensitive information
20. Write encrypted data to tables or Parquet files
21. Manage sensitive information

Executing Data Engineering

Designing, building, and maintaining high-performance, scalable, and secure data solutions
•Designing and developing data pipelines and ETL processes
• Build and maintain data warehouses and data lakes
• Optimize data performance and scalability
• Design and implement a new data architecture to be scalable, resilient, and secure.
• Data architecture
• Cloud computing (AWS, Azure, GCP)
• Data modeling (conceptual, logical, and physical)
• Data governance
• Data engineering

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Steps

We work agile by bringing people, processes, technology and context together to find the most appropriate and effective solutions for clients vision and IT strategy.

1

Specification

First Meeting with the client to learn about the project goals and budget.

2

Consultant(s) Digital Card and Statement of Work (SoW)

We will deliver the consultant(s) business card as well as the statement of work (SOW) with clear definition of work being provided, prices, scope , project deliverables, work location, timelines and payment terms and conditions.

3

Delivery

After Avilius receives the SoW approval and a successful Purchase Order that confirms the purchase of services stated in the S0W, our consultants will start working on the deliverables agreed in the Statement of Work .

4

Change Requests

We work agile and are extremely flexible, the client can always approach and discuss new changes requests to the initial Statement of Work. Avilius will work with you to onboard the new change request in the initial scoped activities.

Services

Contacts

Email: info@avilius.nl

Data Engineering