Agile data method


Agile Data Method: Effective Strategies for the Agile Developer

Agile Data Method: Effective Strategies for the Agile Developer

Agile methodology is a lightweight approach to software development which promotes rapid, short-cycle, iterative approach with deep involvement of all stakeholders in the process. Agile practices work great with complex projects which need to be done over a brief period of time. Choosing Agile, you choose flexibility, high adaptability to changing environment, constant interaction, and evolutionary development. Agile methods are abundant, and they can be used to develop any kind of software, including data-oriented software.

Agile data method is an Agile approach which focuses on a combination of principles which help develop data-oriented software.

There are six principles defining this method:

1. Data. When developing software with Agile data method, you have to keep in mind that data is the most important feature of software-based systems. Obviously.

2. Enterprise issues. Before using Agile data method, the development team must make sure that the enterprise has enough resources to fulfill the project. Have enterprise issues in mind before using this method.

3. Enterprise groups. Enterprise groups should constantly interact and stay agile throughout the whole project.

4. Uniqueness. Remember that each software development project is unique, so you should not carbon-copy your methods from one project to another. A tailored approach to each task is required.

5. Teamwork. Agile methods require professional developers working in collaboration with each other, other teams and the customer.

6. Sweet spots. Find compromise solutions for any issue; avoid painting the project black and white.

Agile methods can use data warehousing. Data warehouse is a database which brings together information from one or several sources to support analysis and reporting. Data may come from various internal sources, such as finance, accounting, and marketing departments or from external sources, such as price lists, social media, websites, etc. The data stored in data warehouses can be interacted with by using different mechanisms, referred to as business intelligence (BI). These mechanisms include query, analysis, dashboards, key performance indicators, etc.

Using Agile methodology for data warehousing allows you to use an evolutionary approach to development and spare a huge amount of costs. In a traditional Waterfall approach, 70-80% of warehouse development budget is spent on data integration and homogenization. It means that you need to accomplish the project before you can interact with data for the first time and realize project’s business value.

With Agile methodology, data warehousing gets simpler. Together with the stakeholders you select a hundred data elements which are the most important for performance and then you scale up your project according to the business needs. By using Agile methodology for data warehouse, you spare resources and provide your customer with workable database pieces which provide value after weeks, not years of development.

The greatest risk businesses face when using traditional Waterfall methods for data warehousing is that the end result may suffer from low adoption rates. In other words, at the end of the day, it may turn out that the final version of the database is not really used by employees.

On the contrary, Agile data methodologies for warehouse ensure continuous delivery of database pieces, so that they can be modified and better integrated into the business structure. Data integration and homogenization – the most time-consuming aspects of data warehousing – are decomposed into smaller tasks which are developed in short cycles, 2-4 weeks long.

By the end of the cycle, development teams present the results of their work and the customer is able to assess it, provide recommendations or even change the requirements. Everyone is winning: the customer participates in the project and makes sure it flows in the right direction, and the developers understand what the customer needs and tailor the product during the development process, not after it.

Building a database with Agile methods requires resources, a lot of preparation and a skilled team. However, if your planning is thorough enough, you will definitely benefit from using Agile data methods and give your customer a more competitive offer than traditional software developers. You may consider resorting to Agile methodology data modeling, a process of exploring data-driven structures, before setting off to develop data warehouse.

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