Big Data

Big Data As A Service

While the data is expected to surge exponentially at all times, organisations need to understand that the volume, veracity, velocity, variety, variability and value aspects of data are also rising. This calls for a reliable and efficient technology that ensures effective aggregation, integration, authentication and appropriate segregation of vital information that helps organisations in dealing with the rapidly changing business scenario.

The relevant data retrieval from the analysis of humongous data constantly in order to drive business growth is what makes the scope of Big Data huge. The massive amounts of data sets that are being created, stored, analysed and acting as a major determinant in various pertinent decision making process in an organisation is called Big Data. Changing the data analysis paradigm is the Big Data technology that encompasses workflows, analytical processes and advanced methodologies to generate useful insights, which further boosts the real time value of a business.

Big Data techniques are designed to transform large amount of structured and unstructured data into comprehensible business data, empowering business owners and analysts to understand, visualise and report the meaningful data to various sources, thus liberating this process from the conventional IT set up.

The tech world is well versed with the terminologies like Software as a Service (SaaS), Platform as a Service (PaaS) and even Data as a Service (DaaS). Up-scaling the quantum of data involved and mixing these technologies gives rise to a whole new concept – Big Data as a Service (BDaaS).

What Exactly Is BDaaS?

In entrepreneurial terms, Big Data refers to implementing the insights filtered from an analysis of huge volumes of data to stimulate accuracy in formation of vital business strategies. Presently, the term BDaaS is quite novice and its usage is limited to outsourcing of the varied Big Data functions to the cloud. This can comprise of supplying of data or analytical tools to cater business needs like interrogating the data and carrying out actual analysis for reporting purposes. There are various BDaaS providers who are dedicated in providing Big Data services along with some consultation and advisory services for helping enterprises to make most of Big Data as a Service.

Potential Of BDaaS

There are various benefits of virtualisation or getting Big Data work outsourced, because storing and managing ever growing large quantities of information demands continuous investment of time and resources. Since BDaaS providers have everything already set up, customers need to just rent the services of their cloud based storage and analytics software and pay them as per the payment policy, where the BDaaS providers take full responsibility of cost of compliance and data security.

The need for Big Data is surging in industries ranging from small, medium to large in the global platform. The rising potential for Big Data implementation is certainly giving a boost to BDaaS providers for offering their expert solutions. 

Step-by-Step Guide To Handle Big Data Projects

1. Devising Strategy 

Power-packed strategy planning becomes a necessity while implementing a new technology and even Big Data requires an extensive planning. With Big Data technology becoming popular at all arenas globally, enterprises are rapidly adopting it as it has created many successful businesses. BDaaS providers examine the cases of Big Data projects in various organisations and determine the options for devising an excellent strategy for the client company. This complete strategy is developed in the presence of prominent shareholders of the company to analyse all aspects and requirements to ensure everything is in line with the project’s successful implementation.

2. Developing Architecture

On devising a suitable strategy on the basis of the needs of the company, a comprehensive architecture must be developed that works in tandem with the primary set of applications. For future applications, Big Data services can be scaled up to alleviate operational efficiency and decision making process in case of work load or business expansion.

3. Data Warehouse Augmentation

Enterprises have to bear the cost of purchasing licenses for proprietary data warehouse that are charged on the basis of appliances deployed or the quantum of Big Data solutions hired. Since enterprises have to pay a reasonable amount in maintaining those data warehouses, BDaaS providers ensure that businesses are able to amplify their warehouses with Big Data solutions like Apache Hadoop. With the help of perfect designing of Big Data and analytics solutions, enhanced performance and economical cost with top notch analytical capabilities becomes possible.

4. Creating Proof Of Concept

Development of proof of concept (POC) application is the next step after designing and architecture work is done. The proof of concept serves as a prototype that showcases how the proposed Big Data project will accomplish the set goals. In this phase, there will be a Big Data testing done on small scale to evaluate the results of the proof of concept. 

5. Application Of Data Science & Analytics

Setting up of Big Data architecture, implementing it to the data store and retrieving the data form one side of the coin. Making use of the valuable insights received in a scientific and organised manner is yet another task where companies would require the expertise of professionals sourced from BDaaS providers. 

6. Gauging The Scope Of Big Data Analytics

Being a novice concept for many businesses, harnessing the true potential of Big Data solutions requires a smart yet cautious approach. Collecting, analysing and extracting relevant data for generating unique business solutions can trigger in better decision making and promote the growth of business.