Big Data Consulting for a Leading Internet of Vehicles Company

About Our Client

The Client is one of the largest Internet of Vehicles companies in the EU that delivers fleet and asset management solutions. The Client collects, stores and processes IoT data from 600,000 vehicles connected to their systems to enable the users of their solutions to make informed decisions.

Challenge

Having a robust IoT data collection and storage solution, the Client was looking to enhance their big data analytics capabilities. Their existing solution is based on Apache Cassandra. Being a key-value storage, Apache Cassandra doesn’t support efficient big data analytics well enough. For example, currently, to retrieve data for 70,000 cars, the Client needs to create 70,000 individual requests that will return 70,000 individual reports, which requires extra efforts to get a complete picture.

Solution

Our big data consultants had a three-day onsite visit to the Client, where they carefully examined the existing solution: its architecture, relevant documentation, available data sources, as well as currently applied data management practices.

As a next step, we held a workshop dedicated to the solution-to-be, where we discussed the expected deadline for the solution launch, the existing and preferred technologies and available licenses. During the workshop, we also laid down architecturally significant requirements concerning the solution’s availability, performance, security, and scalability. Then, we prioritized each requirement describing their impact on the Client’s business as critical, high, medium or low.

Based on the workshop’s findings, our consultants designed the architectural concept of the solution-to-be. We defined high-level architecture components, for example, integration services and a data lake, and described their functions.

After presenting the concept of the solution, our consultants organized a Q&A session where we provided comprehensive answers on any aspect that the Client was interested in. For instance, we explained the advantages and disadvantages of a data lake compared to a data hub. We also compared on-premises implementation against cloud options, including different cloud scenarios – with Amazon Web Services and Microsoft Azure at the core.

Besides, our Apache Cassandra consultants provided the Client with recommendations on how to improve Apache Cassandra’s performance, which embraced such aspects as the structure of tables, partition keys, as well as the format of data to be stored.

Results

The Client received a visit report that contained the following:

• Architecturally significant requirements for the solution-to-be and their impact on the business.
• High-level design of key architecture components with their functions described.

The Client received comprehensive answers to their questions concerning the future solution’s implementation, the pros and cons of different technologies and architecture components, the nuances of data storage and integration, and other important issues.

Methodologies

Business requirements analysis, functional decomposition, workshop on architecturally significant requirements, Q&A session, comparative analysis of technologies.