CLOUD COMPUTING | DATA PROCESSING | DATA RESEARCH & ANALYTICS | OUTSOURCING SOLUTIONS
Bullseye provides comprehensive outsourcing solutions for data collection, processing, storage, research, analytics and cloud computing. Bullseye uses state-of-the-art, carrier neutral tier III data center with 99.995% uptime guaranteed facilities which are equipped with modern and cutting-edge hardware technologies to deliver robust, resilient and cost effective industry data centers and cloud hosting solutions. Our comprehensive cloud migration framework brings industrialized capabilities together with exclusive tools, methods, and automation across all cloud varieties (public, private, hybrid) and multiple delivery methods (IaaS, PaaS, and SaaS).
For many organizations getting value from the increasing volumes of data remains a challenge. With the rapid growth of emerging applications like social network analysis, semantic Web analysis and bioinformatics network analysis, a variety of data to be processed continues to witness a quick increase. Effective management and analysis of large-scale data poses an interesting but critical challenge. The answer to these challenges is a shift to Cloud technology. Digital transformation initiatives, expansion of machine learning programs, and of late the growing cult of “work from home” have been facilitated by this shift to cloud computing. The main priorities for these initiatives and programs are improving data security and threat protection, optimizing customer experience, and predictive maintenance.
Our activities start with collection of data in its raw form which is then aggregated, enriched, transformed, filtered, cleaned and converted into a more readable format (graphs, documents, etc.), giving it the form and context necessary to be interpreted by computers and utilized by employees throughout an organization. Near-constant technology and software updates mean more data, which makes our data processing activities even more important and much sought after. Listed below is our step by step procedure:
Data Collection : Collecting data is the first step in data processing. Data is pulled from available sources, including data lakes and data warehouses. Special care is taken to make sure that the data sources available are trustworthy and well-built so the data collected (and later used as information) is of the highest possible quality.
Data Preparation: The collected data then enters the data preparation stage at which raw data is cleaned up and organized for the following stage of data processing. During preparation, raw data is diligently checked for any errors to eliminate bad data (redundant, incomplete, or incorrect data) and begin to create high-quality data suitable for business intelligence.
Data Input: The clean data is then entered into its destination and translated into a language that it can understand and begins to take the form of usable information.
Data Processing: Inputted data is then processed for interpretation. Processing is done using machine learning algorithms. synchronizing all the data entered into the software in order to filter out the most useful information out of it. By implementing proper security algorithms and protocols, we ensure that the inputs and the processed information is safe and stored securely without unauthorized access or changes.
Data Output/Interpretation: Data is finally usable. It is translated, readable, and often in the form of graphs, videos, images, plain text, etc.). Members of the company or institution can now begin to self-serve the data for their own data analytics projects.
Data storage: After all of the data is processed, it is then stored for future use in compliance with GDPR. Integrated Cloud Technology builds on the convenience of current electronic data processing methods and accelerates its speed and effectiveness. Faster, higher-quality data means more data for each client organization to utilize and more valuable insights to extract.
From data processing to analytics
Big data is changing how all of us do business. Today, remaining agile and competitive depends on having a clear, effective data processing strategy. While the six steps of data processing won’t change, the cloud has driven huge advances in technology that deliver the most advanced, cost-effective, and fastest data processing methods to date. As big data migrates to the cloud, client companies are realizing huge benefits. Big data cloud technologies allow for client companies to combine all of their platforms into one easily-adaptable system. As software changes and updates, cloud technology seamlessly integrates the new with the old. The benefits of cloud data processing are in no way limited to large corporations. In fact, smaller client companies can reap major benefits of their own. Cloud platforms are inexpensive and offer the flexibility to grow and expand capabilities as the company grows. It gives companies the ability to scale without a hefty price tag.
Whether you’re a business, organization, agency, entrepreneur, researcher, student, or just a curious individual, gathering data needs to be one of your top priorities. Still, raw information doesn’t always have to be particularly useful. Without proper context and structure, it’s just a set of random facts and figures after all. If you, however, organize, structure, and analyze that data, you’ve got yourself a powerful “fuel” for your decision-making. The future of data processing lies in the last step of the process - storage. Data needs to be quickly and easily accessible, so many businesses are looking toward the cloud. Cloud technology improves upon the current electronic data processing methods, thus making it faster and more efficient. The cloud is especially beneficial for big data - that is, data that is too large for traditional data processing. As IoT and mobile devices surge in popularity, it's also become synonymous with gathering, analyzing, and using huge amounts of digital information for business operations. People are producing more and more data, and datasets are becoming larger every day. Because of this, the cloud is the natural next step for data processing. The cloud's most important selling point is perhaps its inherent adaptability. Technology is constantly evolving and updating, so data processing systems need to be able to adapt quickly. The cloud can easily incorporate software updates and allows companies to combine all of their platforms into one system. While the cloud is already being used by major big data corporations, smaller companies can benefit from using the cloud as well. Because of their flexibility, cloud platforms provide smaller companies with an opportunity for growth. They can also be quite inexpensive, so cost is not necessarily an obstacle.
Businesses are quickly discovering that traditional data management systems and strategies are no longer capable of supporting their demands…a new generation of cloud-native, self-service platforms have become essential to the success of data programs, especially as companies look to expand their operations with new artificial intelligence, machine learning and analytics initiatives. Bullseye's extended capabilities provide some stunning solutions:
✔ CI/CD Tools & Pipeline Automation
✔ Integration with existing tools
✔ Containerization and Orchestration
✔ Build Once Deploy Many model
✔ Managed services for public & private cloud
✔ Monitoring the ongoing operations
✔ Automation experience
✔ ITIL support processes
✔ Enterprise Architecture and Roadmaps
✔ Cloud Readiness Assessment
✔ Infrastructure as Code
✔ Blueprints and DevOps Platform
✔ Brownfield Application assessments
✔ Migration strategies
✔ Technology Refresh
✔ Application Architecture
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Sector-48, Sohna Road, Gurgaon, HR 122018, IN
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Sector-48, Sohna Road, Gurgaon, HR 122018, IN
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