Agile Analytics: The Ultimate Guide [+6 Learning Resources]

In a fast-paced business environment, data changes every second. Extracting value from ever-changing data sets requires applying agile analytical techniques.

Today, companies are making operational, marketing, sales, and product development decisions quickly to adapt to ever-changing market dynamics.

This is where agile analytics for data analysis comes into play. This provided a proven framework for extracting actionable insights from data collected live and analyzed in sprints, similar to agile software development processes.

If you haven’t yet learned the basics and advanced concepts of agile business analysis, keep reading until the end.

Agile analysis and its principles

Agile business analytics is a source approach that analyzes data using rapid, iterative cycles of analysis. Seek customer feedback and rework your analysis to make better decisions about project and product development progress.

Parent agile product development projects no longer have to wait months for actionable data insights from data analysis projects. Instead, they receive frequent input from the BI team to ensure the final product is in line with market trends.

This works similarly to the Agile or Scrum software development lifecycle. BI Analysts are required to perform all data analysis processes such as data sourcing, data cleaning, data reduction, storage, wrangling, ETL scripting, visualization, and insight reporting in short sprints.

The main objective is to leverage real-time data. Therefore, product or software development teams and business operations teams have access to living data insights compared to old business insights in traditional data analysis processes.

Advantages of agile analysis

Transparency and efficiency

Following an agile business analysis process allows you to discover defects and errors on a regular basis. Therefore, you can improvise your workflow and achieve perfect performance in future sprints.

Easy delivery

By following this framework, you can deliver more BI reports in less time. Data analysis teams can split datasets into smaller chunks and analyze those chunks independently but collaboratively on an ongoing basis.

Simply combine individual results into a single report to create a complete picture or forecast.

collaborative approach

Agile analysis relies on extensive collaboration. Therefore, teams need to follow the correct project path to avoid datasets accumulating in silos.

better business decisions

Your own business or clients can take advantage of data insights from real-time data rather than stale data to make timely and effective business decisions.

Deliver timely insights

Get data insights into your business dynamics exactly when you need them. For example, when the requirements for virtual meeting apps increased during the COVID-19 pandemic, apps that use agile analytics became popular.

This BI approach helped the company understand trends and roll out a minimum viable product faster than its competitors.

Why should I adopt agile analytics?

Following a traditional business analysis approach may seem promising because the process seems easy. Set goals, collect data, and analyze the data to justify your goals or provide insights to achieve them.

However, there is a fundamental problem with this BI methodology. Data analysis teams can spend too much time setting up tools to manipulate and visualize data. In some cases, it can take a team several months to complete a few lines of code for data analysis.

After completing all the other steps in the data analysis project cycle, you will have some business insights, data patterns, or data models that may or may not support the assumptions and goals you set at the beginning of the project.

By this time, the market had changed significantly. New demand will be created, and the product or service you have developed will receive less attention.

Therefore, you need to implement an agile analytics framework to process raw data into useful analytics in short sprints. If you can minimize sprints within a few days or up to a week, that’s great.

How to implement agile analytics

Implementing agile business analytics should be similar to implementing the parent software or product development project. Follow the five stages of the agile framework. It is as follows:

• First, you need to find the best way to analyze your data according to industry standards. You also need to choose an efficient BI tool at this point.
• The second phase involves creating a list of key requirements, identifying data sources, cleaning datasets, and creating an initial set of dashboards for stakeholder review.
• The third phase is all about standardizing key business intelligence tasks. For example, you need to streamline data sources, databases, IT infrastructure, ETL processes, data extraction, data security, and more.
• The fourth phase involves scaling the output of data analytics, such as dashboards, graphs, and cloud dashboards.
• The final phase is supporting teams or clients who use the dashboard for further business reasons. Also, during this phase you need to collect feedback and inform the next sprint.

Best practices for agile analysis

The results of agile analysis directly impact business decisions, so you should follow the proven and risk-free path of agile analysis. Here are some best practices that successful top companies employ within their organizations.

#1. Incremental delivery

As the name suggests, agile analytics is the practice of analyzing data in short sprints to discover optimal value from real-time datasets.

To make the data analysis process more efficient and cost-effective, agile teams need to be able to incrementally deliver insights, reports, data models, data-backed business decisions, performance analysis, and more. there is.

#2.Ready to accept changes

You must develop a mindset within your team that market dynamics will change as the project progresses. Therefore, teams may need to adapt as changes occur.

The ultimate goal is to create timely and effective data analysis reports for current market conditions.

#3.Frequent delivery

Data analytics teams must ensure that they deliver a minimum viable product or MVP at the end of every week or two. This ensures that the entire agile development process can benefit from the analysis of real-time datasets.

#4.Agile collaboration

The data analysis team must be ready to collaborate with all stakeholders on the project. You need an online collaboration tool that allows you to easily collaborate as soon as you meet your requirements.

These are important best practices that any agile analytics project, team, or company should follow. Here are some additional practices that will help you succeed in this area.

• Create an environment that supports business intelligence analysts.
• Data analytics teams also need to ensure reliable data and patterns for downstream processes to ensure that related tasks and subtasks do not have adverse effects.
• Managers of agile analytics teams must ensure that projects are on schedule, budget, and scope.
• Innovating agile sprints for data analysis and report generation requires making the process more error-free, adapting to previous feedback, and delivering better results than the last sprint.
• When there are significant changes on the client side, all teams must work together to improvise the project path to minimize project costs.

Agile Analytics: Learning Resources

#1.Agile Analysis | Coursera

This Agile Analytics course from Coursera will help you build a powerful analytics infrastructure for your team so you can create more value by integrating it into the core of your business.

From this resource, you’ll also learn how to naturally integrate your workflow with actionable analytics, combining personas and problem-centric hypotheses with your analytics. This course will take approximately 15 hours to complete.

The course language is English, but subtitles are available in Arabic, French, Italian, German, Russian, Spanish, etc. Additionally, if you don’t have time for your coursework, you can reschedule your deadline. This course is 100% online and you will receive a shareable certificate upon successful completion.

#2. Become an Agile Business Analyst with Scrum | Udemy

This Udemy course will help you learn the BABOK guide to agile scaling concepts and standards. You can also use your knowledge to become an AAC Certified Professional.

Additionally, you will learn key business analysis techniques such as product roadmaps, user personas, user stories, retrospectives, MVP, and Kano analysis. This resource will also help you understand what an agile business analyst does and how they work.

Therefore, you can adapt to the agile mindset required of a business analyst. This course consists of 13 downloadable resources, 9 articles, and 3 hours of on-demand video material. You will also receive a certificate of completion and lifetime access to all materials.

# 3.Agile analysis

This book shows you how to carefully adapt traditional agile methodologies to address the unique requirements and attributes of DW/BI projects. We provide knowledge on how to leverage agile methodologies to improve innovation, value, and quality in any project (analytics, data warehousing, business intelligence).

preview	product	evaluation	price
	Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing (Agile…		$39.10	Buy on Amazon

Here the authors introduced a platform-independent agile solution. This helps integrate diverse operational, legacy, and specialized infrastructures. This resource provides practical examples of managing analytics development teams with diverse skill sets. After reading this book, you will be able to cope with the rapidly increasing amount of data.

This book describes proven solutions for IT professionals, database administrators, data warehouse professionals, BI specialists, or database developers. It also helps improve business alignment, reduce business risks, and achieve better results.

#4.Analysis : The Agile Way

Even if you’re using analytics, if you look at things from a traditional IT project perspective, that’s not the right way to do things. Read this book to learn how industry giants like Google and Nextdoor approach modern analytics.

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	Analytics: Agile Methodology (Wiley and SAS Business Series)		$32.57	Buy on Amazon

This resource also describes how these organizations are applying agile analysis methodologies beyond traditional areas such as engineering and software development. As a result, employees at these smart companies are able to understand and act many times faster than traditional employees.

This book uses the perfect combination of case studies, examples, and exercises. It also shows how this fresh way of thinking can open the door to huge opportunities. If you’re in an organization that embraces uncertainty and is ready to adapt to a fast-paced world, this is the ideal book for you.

#5. How to become an agile business analyst

This book is about implementing business analysis skills using Agile. Don’t be fooled by the name of this book. Agile here means an approach, not a methodology.

preview	product	evaluation	price
	How to become an agile business analyst		$27.89	Buy on Amazon

This resource enables business analysts to become agile and effective team members. Learn how to apply your skills to add value to your team. In this book, you’ll also learn about the five characteristics of an agile business analyst. It also explains how to incorporate those characteristics.

Additionally, this resource will also explain your role and responsibilities and help you explore the impact of agile approaches on your regular business analysis processes. If you follow this book correctly, you will prove yourself to be a useful member of your team.

#6. Data Curious: Applying Agile Analytics

Citizen data analysts are filling the gaps left by traditional business intelligence processes. However, these new data analysts do not have a background in data processing technology. This book will help these professionals fill in the gaps in their knowledge.

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	Data Curious: Apply agile analytics to improve business decisions	No ratings yet	$34.48	Buy on Amazon

Learn the basics of data literacy. As a result, tech-savvy business professionals will be able to understand the possibilities and ask the right questions.

Additionally, this resource provides practical advice to help your team become self-reliant and bring about positive change.

conclusion

Agile analytics is your best bet for gaining a competitive edge in your industry. This allows you to make timely decisions in less time and without making mistakes.

Data analysis teams can also efficiently analyze large datasets coming from multiple directions by following an agile data analysis process.

Try out any of the virtual learning courses or books listed above. These will help you gain knowledge and confidence in agile analysis that can be applied to real-world business cases.

Next up is the best business intelligence platform and edge analytics.