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How to Use Big Data in Agile Methodologies

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The cutthroat competition that marks today’s marketplace has forced many companies to change their strategies in handling Big Data. Indecision is no longer an option in an environment where slight delays can result in lost business opportunities. Companies need a clear understanding of their customers and what they can do to their products and services to make these customers purchase more, as well as encourage people in their circles to do the same.

To do this, companies are embracing prescriptive and predictive technologies to analyze all their real-time data and help them make better business decisions. The data includes data from social networks like Facebook and Twitter, data from the comments section on websites, product review websites, open data, client data, navigation logs, geolocation data, wearables, sensor data, and customer calls to business calls centers, etc.

Some of these data are structured, while others are unstructured. The volume also varies. To store and analyze this data in a way that can positively impact the business, businesses need new technologies with analytical capabilities. For instance, imagine the data a business can collect from Facebook where millions of people publish comments and opinions. If analyzed, this unstructured data can help a business better understand its customers.

What is Agile methodology?

To gain insights into the data, including understanding why customers are dissatisfied with one brand and impressed by another, the business needs to have a methodology that is able to handle the fluid interaction of data engineers, data architects, visualization experts, and data scientists. This multidisciplinary team can make available an analytical methodology capable of an exhaustive analysis of all available data and be producing helpful results for the business.


An agile methodology is a time-tested software development and business process management approach that many IT organizations use to increase efficiency and improve products and services. Agile is a concerted approach to development, where cross-functional teams work together to design and build application features and minimally viable products (MVPs), testing them with their customers, and rapidly and repetitively enhancing and refining them.

Benefits of Agile methodology

When applied to Big Data, agile brings collaboration to development and delivery. Agile methodology allows cross-functional teams in a company to work together to generate reliable insights into the company’s customers so that the leadership can figure out how to address its biggest challenges in selling its products and services.

Adopting agile methodologies in the context of big data allows the extraction of valuable information from available data in a precise and quick way. Essentially, the data is converted to knowledge that can be immediately used to make path-altering decisions for better business performance. With this approach, business leaders can integrate big data into the existing business strategy and give their company a competitive advantage.

The ideal agile methodology platform for big data should have the following capabilities:

  • Must be able to handle data in real-time and in a continuous stream
  • Must have the capacity to dynamically construct and maintain several agile views of available data so as to satisfy the set application requirements
  • The agile views need to maintain the integrity of the data
  • The agile platform should simplify the application code by isolating the complexity of the schema from the application developers
  • The big data infrastructure needs to be reliable and fully scalable. It should have the capacity to stream both dynamic and processing views
  • The agile big data platform should have the capacity to handle event processing
  • It should be possible to access all views via advanced dashboards and in real-time
  • The practices and principles of agile methodology focus on confirming assumptions the earliest possible during a project delivery lifecycle. Doing so reduces the prevailing risk exposure in the undertaking of the project.
  • Some of the benefits of agile methodology in big data include:
  • It helps in de-cluttering a company’s information landscape
  • Makes it easy to access and combine data from several business units, functions and databases
  • The rapid iterations of MVPs provide immediate value to the business
  • The deep insights into the business data create new growth opportunities for the business
  • Helps IT organizations in prioritizing digital and data transformation initiatives
  • Brings unparalleled visibility into business data to all decision-makers in the business organization

To reap the benefits of agile methodology, business executives should give their cross-functional data teams considerable leeway to decide on the approach to take in data architecture and migration. If possible, the executives should create direct communication channels between them and these cross-functional agile data teams. This would improve the speed with which emerging concerns are addressed.


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