Big Data Architecture and
Solutions
Every organisation keeps its data at a repository for quick and easy access. These days, organisations are getting more and more data from multiple sources and if data is too big, it becomes difficult to store that.
Big Data is a data that is too large and complex for the conventional tools to collect and manage. Thereby, organisations are rethinking their approach towards traditional tools to leverage data. For this reason, Big Data Architecture is deployed and used for analysing terabytes and petabytes of data.
Orchid Solutions provides qualitative and innovative solutions to its clients. We provide end to end solutions for Big Data Architecture for our customers. Our professional approach can generate more actionable insights from Big Data. We build the Big Data Architecture around essential components such as an integrated warehouse and a platform for analytics. This bridges the gap between the raw data sources and BI tools. This also helps to reduce the complexity and enables the company to leverage fast- moving data. Thereby, allowing the right person to access and analyse data in an efficient manner.
What is Big Data Architecture?
Big Data Architecture is a conceptual or graphical representation of how big data will be stored, managed and accessed. Typically, it defines how the big data solutions will work and outlines the hardware, software and database components. Big Data Architects before implementing a big data solution, strive to understand the technical and strategic requirements of their clients. Big Data Architecture has a mechanism to transform data into database structures. Typically, architecture has multiple layers for big data solutions.
- Big data sources layer- This layer consists of the sources of big data. The data source can be data warehouses, mobile devices, MS Office documents or e-mail. In this solution, big data can be absorbed in batches and in the real-time.
- Storage layer- Data from the source layer is received by this layer. It can convert unstructured data to an understandable format.
- Analysis layer- The stored data is analysed to extract useful information in this layer. There are multiple tools that operate for this purpose.
- Consumption layer- The analysis results are received by this layer and are transferred to the output layer. This layer can consist of human, applications or business processes.
Should you opt for Big Data Architecture?
Big Data Architecture is required by those who analyse terabytes of data from multiple disparate sources, run computing tasks for a longer period of time, and want to extract information from extensive networking or have multiple large data sources for analysing data. Big Data Architecture is very useful for the organisations with such requirements. It is deployed for performing analysis and delivering results to the businesses.
We always make an effort to improve the services we render and install customised solutions towards Big Data Architecture for its clients. We think of long term commitments and deploy the Big Data Architecture, which is comprehensive. This would be capable of solving many business problems that might arise in future. We offer our services at competitive prices in agreed timelines and also provide guaranteed support to the clients.
Why Choose Orchid?
For Big Data Architecture solutions, we have an accomplished team to incorporate new varieties for the expanding volumes of data.
- You can make data substantial for your business with our high quality and affordable Big Data Architecture solutions.
- We have expert data analysts and data architects for understanding your business requirements and big data needs. Thereby, developing and deploying the solutions according to the needs of the businesses.
- We help you reduce costs by integrating the new technology with the existing data architecture.
- We can develop streamlined Big Data Architecture to bring new solutions on board the already existing infrastructure.
- With the technology we offer, you can address many initiatives of the organisation and scale up the expertise and skills required for new projects.