CMMI Level 3 Company
The advancements in machine learning and artificial intelligence have boosted prospects of automation and highlighted the significance of data in a fast-evolving business environment. Data is poised to play an important role in the enterprises of the future, with businesses looking to scale up production and recover costs with maximum efficiency and minimum by leveraging powerful predictive models. The dependability on data has increased ever since customers and businesses started interacting in real-time, by leveraging diverse technology platforms. According to a forecast for the year 2020, data has been growing at a mind-boggling rate. By then, new data –at least the size of a standard audio track - will be created every second for each living human on the planet.
Large sets of structured and unstructured data require complex methodologies for processing, and can be handled efficiently using sophisticated software and tools that can facilitate their storage and retrieval. Specific Big Data applications such as Hadoop allow enterprises to automate their processes and pursue rapid business transformation. Big Data tools are used extensively across service-oriented sectors such as telecommunications, banking and retail; in addition to several more.
The principals that govern data assortment, processing, and analysis, driven by well-defined algorithms and business engine rules; are collectively studied as Data Sciences. This area of knowledge manifests as an ‘umbrella’ of principles from statistics, programming, and data extraction along with underlying data analysis. This allows us to consider a range of possible business scenarios in order to choose the most viable option and the most recommendable action.
Data Sciences is being applied in a number of powerful technology products and application-based scenarios. Few of the prominent ones are listed below:
A capable Data Scientist is supposedly well-versed with several associated disciplines, including in-depth knowledge of statistical techniques and advanced tools such as SAS or R, along with the Hadoop data-processing platform and proficiency in Python language, along with zeal to work with unstructured and scattered forms of data.
The various forms of processed data and the diverse insights that can be generated can be applied in numerous ways, thanks to advanced forms of data skewing and number crunching that are driven by advanced analytics. This helps in drawing inferences and meaningful patterns on customer behavior in order to achieve short-term and well as long-term objectives with respect to overall business strategy in terms of market penetration, pricing, and product differentiation.
A number of businesses currently leverage Data Analytics in order to streamline their processes and key objectives:
Raybiztech is a leading Global Information Technology (IT) Services and Solutions, a CMMI Level 3, ISO 27001:2013 and ISO 9001:2015 Certified Company. We are a Member of NASSCOM, HYSEA, NJTC, and AIIA. Raybiztech offers comprehensive end-to-end IT Services for Business Application Development, Enterprise Solutions, Enterprise Collaboration Services, Testing and Quality Assurance Services, Cloud Computing and IT Infrastructure Management to organizations in the Banking & Finance, Insurance, Healthcare, Manufacturing, Retail, Media & Entertainment, Leisure & Travel, Telecom and Energy & Utilities verticals as well as Independent Software Vendors.
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