With our Big Data Services and Solution we make collaborative efforts to bring order to your Big Data while our team of senior-level consultants helps in implementing the technologies required to manage and understand your data, enabling you to predict customer demand and make better decisions at the right time. Analyzing your business challenges well, we offer you the strategic guidance needed to succeed, leveraging the power of data you accumulate, to your advantage. We follow best industry standard of big data solution implementation as mentioned below.
System Orchestration is the automated arrangement, coordination, and management of computer systems, middleware, and services. Orchestration ensures that the different applications, data and infrastructure components of Big Data environments all work together. In order to accomplish this, the System Orchestrator makes use of workflows, automation and change management processes.
The Data collector plays a vital role to collect new data or information feeds into the Big Data system for discovery, access, and transformation by the Big Data system. The data can originate from different sources, such as human generated data (social media), sensory data (RFID tags) or third-party systems (bank transactions).
One of the key characteristics of Big Data is its variety aspect, meaning that data can come in different formats from different sources. Input data can come in the form of text files, images, audio, weblogs, etc. Sources can include internal enterprise systems (ERP, CRM, Finance) or external system (purchased data, social feeds). Consequently, data from different sources may have different security and privacy considerations.
The Big Data Application architecture component that contains the business logic and functionality that is necessary to transform the data into the desired results. The common objective of this component is to extract value from the input data, and it includes the following activities:
The extent and types of applications (i.e., software programs) that are used in this component of the reference architecture vary greatly and are based on the nature and business of the enterprise. For financial enterprises, applications can include fraud detection software, credit score applications or authentication software. In production companies, the Big Data Application Provider components can be inventory management, supply chain optimization or route optimization software.
The Big Data Framework is then developed based on the resources and services that can be used by the Big Data Application Design, and provides the core infrastructure of the Big Data Architecture. In this component, the data is stored and processed based on designs that are optimized for Big Data environments.
The Big Data Framework Provider can be further sub-divided into the following sub-roles:
Similar to the Data Collector, the role of Data Consumer within the Big Data Reference Architecture can be an actual end user or another system. In many ways, this role is the mirror image of the Data Collector. The activities associated with the Data Consumer and API development include the following:
The Data Consumer uses the interfaces or services provided by the Big Data Application Provider to get access to the information of interest. These interfaces can include data reporting, data retrieval and data rendering.