Big Data & Data Engineering
We are surrounded by “smart” gadgets, machines, household appliances, and assets equipped with a variety of sensors. To fully benefit from this intelligence, any new technology your organisation adopts must be able to handle the large volume of data from these sensors, even when they are gathered in different speeds and formats.
And it doesn’t stop there. Combine these data sources with data from website statistics, log data, and more, and you have a data explosion that forces us to rethink technology and how it fits into our data and analytics architecture.
What is Big Data & Data Engineering?
Big data & data engineering refers to handling data sets that traditional relational database systems cannot efficiently manage. Together, Big Data & Data Engineering deliver advantages and enable new business use cases.
Your organisation needs Big Data & Data Engineering
Even if your relational database system can store large amounts of data, there’s no denying that Big Data & Data Engineering are becoming increasingly important for numerous reasons, including:
- Cost: storing large data objects in a relational database is expensive. Depending on the use case, you can store Terabytes of data for just a few euro per month
- Data format: big data technologies do not force the source data to fit a specific format. Instead, you only define your data scheme when you need it. In other words, you define your schema-on-read, instead of the traditional schema-on write
- Separation: by separating storage from compute, you only have to pay for the expensive part (the compute) when you need it
- Languages: data engineering tools speak more languages, including Python, R, Scala, and SQL
Implementing Big Data & Data Engineering
Are you looking to integrate Big Data & Data Engineering into your existing architecture? Aivix helps you to gain value from your data, fulfil your business needs, and is as futureproof as possible. By mapping your data use cases on your technological architecture, Aivix ensures the right tool is used for each job.
For instance, big data technology is ideal for crunching large amounts of unstructured data every night, while a traditional data warehouse is better when you have an aging balance of your receivables from your ERP.
How Aivix can help you with Big Data & Data Engineering?
Are you taking your first steps towards handling Big Data & Data Engineering? Aivix offers a range of services, including collaborating to find the best architecture for your use case and the practical implementation of your selected technology. Our team of experts are also ready to configure the services and connections needed to transform your data and add even more value to your organisation.