Big Data Development

Big Data Development

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Our experienced Big Data consultants and engineers support an end to end implementation of the Big Data Projects. We make collaborative efforts to bring order to your Big Data. 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.

We handle all the stages of Big Data development – Data Acquisition and Ingestion, Big Data Storage, Data Processing, and Data Visualization. Be sure that you get our professional advice about whether to deploy the solution on-premises or in the cloud platform. We help you calculate the required size and structure of clusters customized to the nature of the implementation. We install and tune all the required frameworks, making them work seamlessly, as well as configure the software and hardware. Analyzing your business challenges well, we offer you the strategic guidance needed to succeed, leveraging the power of data you accumulate, to your advantage.

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Big Data Ingestion

Big Data ingestion is a process of connecting to disparate sources, extracting the data, and moving the data into Big Data stores for storage and further analysis. We are experts in prioritizing data sources, validating individual files, and routing data items to the correct destination. We choose the most appropriate tool specific to a project out of multiple options available from open source data ingestion tools or tools provided by cloud solutions providers or building a data ingestion tool.
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Big Data Storage

Big Data storage is concerned with storing and managing data in a scalable way, satisfying the needs of applications that require access to the data. The ideal Big Data storage system would allow the storage of an unlimited amount of data, cope both with high rates of random write, and read access. The storage system flexibly and efficiently deals with a range of different data models, supporting both structured and unstructured data. There are challenges like Volume, Velocity, Variety in storing Big data. We address these challenges by making use of distributed, shared architectures. Choosing an optimal storage system allows addressing increased storage requirements by scaling out to new nodes providing computational power and storage.
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Big Data Processing

Big Data processing encompasses a set of techniques used before the application of a data mining method as large amounts of data are likely to be imperfect, containing inconsistencies and redundancies and not directly applicable for starting a data mining process. Big Data processing includes a wide range of disciplines, data preparation, data reduction techniques, data transformation, integration, cleansing, and normalization. We have vast experience in applying the optimal techniques by choosing the appropriate tools to process the data as per the client project needs. After the application of a successful Big Data preprocessing technique implemented by our team, the final data set obtained is reliable and suitable for any further processing or downstream applications.
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Big Data Visualization

Big Data visualization refers to the implementation of more contemporary visualization techniques to illustrate the relationships within data. Visualization tactics include applications that can display real-time changes and more illustrative graphics, thus going beyond pie, bar, and other charts. We can seamlessly integrate the suitable visualization tools with the processing tools to depict the insights or patterns.