Big Data Services

Big data is a proven yet emerging technology that enables organizations to analyze structured, unstructured, and semi-structured data produced from a variety of internal and external sources. Existing analytical solutions, including the infrastructure and methodology, are inclined more towards descriptive analytics. Organizations can leverage big data technologies to extend their analytical capacities to the rest of the analytics continuum beyond descriptive to: diagnostic, predictive, and prescriptive.

The complete spectrum of analytics, powered by big data technologies, cannot only support internal business decisions like traditional analytics but it can also minimize the execution time of the massive computing task, improvise business processes, produce drastic cost reductions, and prescribe new product and service offerings.

How we work

Vinformatics offers a proven solution, to overcome pitfalls of data migration projects.
The primary objectives of the data migration project are to extract the data from the legacy system, transform it into the desired target data model, and finally to upload into the new information system. However, it needs an agile and proactive solution model to overcome unique challenges of data migration.
Vinformatics offers a proven solution, to overcome challenges of data migration projects. Based on the lesson learned from my experience and the best practices for data migration, recommend by veterans and industry experts.

Challenges

The term ‘big data’ has gained the reputation of being a game changer. However, due to the vague terminology, ideating its effects on an industry or a particular organization is difficult. ROI-driven companies cannot afford an experimental and discovery-oriented big data project if it is not going to solve any business problem. Therefore, organizations have to identify the business area that can lead the big data initiative and strategize the objectives with a definite project management plan. Thus, big data can be a game changer only if executives are willing to change the game.

Confusion

Success stories of big data across industries have induced substantial interest from executives and business managers. However, managers or executives intrigued by the possibility of big data can find it troublesome to get started with the technology. Blown away by new jargons every quarter for some new big data technology with over-the-top promises, leading a big data initiative is more often than not confusing for managers. Over time, this confusion has led to increased sales of data visualization tools (a type of descriptive analytics) often wrapped in the big data tag.

Solution

Vinformatics offers consulting services to organizations seeking the right strategy to initiate big data projects. Our ‘Test the Big Data Waters’ service is a six- to-eight week pilot project with clear deliverables. The objective is to evaluate the big data readiness of all or pre-specified business units and identify the best business unit that can be explored with big data technologies at a minimum capital cost and visible ROI. Leveraging the deliverables of this project, the business can build a contemporary data analytics platform, which forms the synthesis between traditional and big data analytics and enables the organization to incrementally augment it with new and disparate data sources for more in-depth analysis.

characteristics of big data

Big data is a collection of data from many different sources and is often describe by five characteristics: volume, value, variety, velocity, and veracity.

Volume

the size and amounts of big data that companies manage and analyze

Value

The most important “V” from the perspective of the business, the value of big data usually comes from insight discovery and pattern recognition that lead to more effective operations, stronger customer relationships and other clear and quantifiable business benefits

Variety

The diversity and range of different data types, including unstructured data, semi-structured data and raw data

Velocity

The speed at which companies receive, store and manage data – e.g., the specific number of social media posts or search queries received within a day, hour or other unit of time

Veracity

The “truth” or accuracy of data and information assets, which often determines executive-level confidence

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