Essential Components of a Modern Analytics Architecture

Essential Components of a Modern Analytics Architecture

Big data is something that is becoming more and more accessible to organisations of all sizes, and there is a strong trend towards functions being carried out in the cloud. This is good news for organisations that want to revamp their analytics approach, because it means that they can take advantage of the massive processing power of cloud servers, and use tools that they would otherwise never have access to.

Essential Components of a Modern Analytics Architecture

What Makes a Great Data Set-up?

Today, the most dominant technology in big data is Hadoop. This is a powerful tool that can be used alongside other technologies to provide powerful data processing. For example, many people use it with Apache Spark for in-memory processing and Apache Hive for data warehousing, as well as HBase NoSQL for storage.

This modern set-up is very fast and highly scalable and can be used to support a lot of data processing. Hadoop offers the ability to store data in a format that is ready for analytics and that can be queried and worked with easily. Performing analytics on Hadoop data is easy and flexible, and it can even be used on top of MySQL, turning an old database into something that can be queried in an accessible and easy big-data way.

Semantic Layers

One of the most interesting things about modern big-data techniques is that you can use semantic layers to turn analysis into something that can be accessible in ‘business language’. For example, why not perform data analysis on ‘high-value users’ - a term that can be configured to mean anything that you want, such as customers that purchase regularly or that have spent more than a certain amount? Every query you run will go through that layer, and the business user doesn’t have to worry about how that is worked out.

With fast processing and user-friendly queries, Apache Hadoop and the associated technology can be a boon to any business. There is something of a learning curve to getting started with this new set-up, but it is well worth it in the end because of the powerful options that it provides for you. There are many cloud-based analytics providers that offer Hadoop and NoSQL set-ups, taking away the complexity of getting started with the infrastructure so that you can focus on the job of handling your company’s data and getting actionable insights from it quickly and easily.


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