A Beginner's Guide to Big Data Architecture
Big data architecture is the structure that contains a business’s big data processing and analytics systems. And, like a building, the way big data architecture is organized will affect everything inside of it. Indeed, there’s more than one way to set up big data architecture, and how a business goes about doing so will influence how they collect, process, and analyze data. First, though, let’s take a look at what big data architecture is and why it matters to companies in the healthcare sector:
Big Data Architecture 101
Big data architecture exists mainly for organizations that utilize large quantities of data at a time –– terabytes and petabytes to be more precise. Single servers can’t handle such a big data set, and, as such, big data architecture can be implemented to segment the data collection, processing, and analysis procedures. There are several different “layers” that comprise most big data architecture models. They are:
- Source –– data must first enter a system through a source. Depending on the company, data may enter a system through servers, third-party sources, or from a separate data warehouse.
- Processing –– within this category there are several smaller subsets. Different big data architectures may process data in batches, in real-time, and/or through stream processing. This step involves transferring unstructured data into structured data.
- Storage –– the data is then stored in what is often referred to as a “data lake.” Some businesses may also use a specialized file such as a Hadoop Distributed File System for storage, for instance.
- Analysis –– once a structured data set enters the analysis layer, businesses can use pre-programmed methods to extract business intelligence solutions from large amounts of raw data.
- Consumption –– the final step of the big data architecture configuration, consumption displays the relevant findings of the analysis.
Types of Big Data Architecture
Though a skyscraper and a baseball stadium may –– on any given day –– contain the same number of people, they are obviously designed for very different functions. Similarly, different types of big data architecture are used by businesses looking for different advantages. There are a number of different ways to build a big data architecture model. Some of the more common varieties include:
- Real-time message ingestion
- NoSQL engines
- Enterprise Data Warehousing
- In-place analytics
Benefits of Big Data Architecture
When it comes to understanding how big data architecture functions, there’s a lot to take in. And we’ve only just scratched the surface in regard to how big data architecture works and the many diverse forms it can take. The good news here, though, is that the benefits of well implemented big data architecture are obvious for large organizations in the healthcare and medical fields. A few major advantages include:
- Reduced costs
- Data scalability and flexibility
- Faster data processing
- Enhanced predictive analytics capabilities
- In-depth data analytics insights
At Amitech, we’re not just big data experts –– we’re big data experts who understand the unique challenges and opportunities before healthcare and medical organizations. We have years of experience in this field and we’re ready to help your team collect, process, and analyze data more effectively. Contact us here for more information.