Best software to enhance businesses' data driven decision making

Huwen Arnone
Aug 3, 2022 4:15:00 PM

Data represents the starting point for taking actions that directly impact business and an entire organization. Data analysis is necessary for the growth of organizations. Consequently, we'll define the concepts related to this area and introduce the leading solutions that are helping companies worldwide make data-driven decisions introducing improvements in their organization.

The effectiveness of data-driven business decision-making depends on the people, followed by the infrastructure where the business strategy is built. Choosing both wisely is a crucial step. This union will allow you to analyze and describe the current situation, its progress and, depending on the organization's maturity, predict specific business scenarios. Let's go through the primary set of attributes that affects this process.

First, it's necessary to define what steps are likely to lead an organization to make decisions in a healthy, data-driven way:

  1. Define business goals.
  2. Identify the data to be used and verify that it's aligned with the business goals.
  3. Select data sources. Clean and organize it.
  4. Establish a data management strategy.
  5. Set what's to be measured and how to achieve it.
  6. Select which tools will manage, process, and visualize the data and how to connect them.
  7. Build visual reports and transform them into information.
  8. Make business decisions based on data.

A couple of points stand out in this list: a differentiation between data and information and the importance of software tool selection for practical business decision-making based on data.
Let's establish the importance of some of these points. Let's explain why:

Data vs Information

Data and information are often referred to interchangeably; although they share certain similarities, they're slightly different terms in this context. The definitions offered by the Oxford English Dictionary are as follows:

  1. Data: "Facts, especially when examined and used to find out things or to make decisions."

  2. Information: "Data that is processed, stored or sent by a computer."

To summarize, data refers to a specific representation of one or a set of attributes; these can be qualitative and quantitative and represent a variety of facts, while information is the set of processed data that communicates what it means. This transformation process is referred to as Business Intelligence (BI).

Therefore, we can state that the expected goal of data analysis is to transform data into information and communicate it in the best possible way. This goal is achieved through the creation of data visualization.

Apart from the data and information terms, there are also Business Intelligence and Data Analytics concepts. What's the purpose of each of these disciplines, and at what point do they collide?

Business Intelligence or Business Analytics?

It's important to differentiate between both concepts in this context, as Business Intelligence is a consequence of the previous Analysis:

  1. Business Intelligence: A practice that enables an organization to transform information into tactical and strategic business decisions. More popularly, this term refers to software tools and services facilitating data transformation.

    Business Intelligence offers the opportunity to answer concrete business questions directly. I.e., "Where is there excess inventory, or Why are sales increasing in X region?"

  2. Business Analytics: It's a set of disciplines and technologies that process and analyze large amounts of accumulated data to visualize trends, patterns, and causes that allow predictions.

    Business data analytics focuses on solving problems by exploring and studying quantitative data models and methods to support data-driven decisions based on business intelligence.Business-Intelligence-or-Business-Analytics-DEISER-ATlassian-Power-BI-Tableau

Software tools to make data-driven business decisions

Using software tools to support BI and analysis processes centralizes data from all organization departments (sales, marketing, finance, people, etc.), establishing each area's performance and how it affects others, and vice versa.

There are many ways to achieve this successfully. The people who analyze and process the data and the decision-makers in the organization are responsible for this. And, of course, supported by the software tool of choice that centralizes the final information.

According to the annual Gartner® Magic Quadrant™ study corresponding to March 2022, there are currently two leading software tools on the market: Microsoft Power BI and Tableau (This same study named Jira Service Management, a visionary solution for IT Service Management in 2021.)

Gartner Magic Quadrant for Analytics and Business Intelligence platforms 2022Gartner Magic Quadrant for Analytics and Business Intelligence platforms 2022

What's Microsoft Power BI?

It's a software tool created by Microsoft that focuses on the cloud and helps manage high volumes and types of data and process it for analysis and visualization.

What's Microsoft Power BI?

Power BI is currently the leading solution in the data analysis tools market; its simplicity in the data cleanup and formatting and the ease of getting data from third-party software tools through native integrations, connectors, APIs, and more, makes it one of the top solutions.

Feeding Power BI with data coming from the software tools where the work from other areas is managed facilitates the data analysis and BI. For example, suppose the Developers team has many projects in Jira. In that case, two apps will bring that information to Power BI, one to track these projects based on specific attributes - to get statistics such as the number of projects, dates, statuses, etc., and another app will extract this data from Jira to Power BI without further effort.

The Desktop option is recommended when getting started with Power BI. It's more basic than the cloud version (according to the Gartner report) and offers good possibilities from the start. For later stages, it's possible to upgrade to complete plans, depending on your needs.

Power BI Benefits

In the following, we'll present the main advantages of working with Microsoft Power BI, a powerful tool for data visualization with a focus on Business Intelligence:

  1. Different users: Power BI can be approached in two ways: as a user, which allows the creation of reports on the data you have fed into the tool, and as a consumer of the reports generated by users, an activity that enables driving BI to make data-driven decisions.

  2. Cost: Power BI offers three plans: Free, Professional, and Premium. The latter provides the option to pay per capacity of data or user. Each plan differs in its characteristics: the higher the plan, the greater depth will get to explore and analyze data.
    For example, the Premium plan, which is the most advanced, allows the creation of automated data flows, data smarts, and the possibility of implementing them in different parts of the world (Cloud), content consumption without licenses per user, and more. If you want more details, please check the pricing plans.

  3. Ease of data extraction, preparation, and modeling: Power BI stands out for its UI/UX simplicity, allowing to connect the data directly to the source and thus optimally debug data visualization through different native sources such as Salesforce, Azure SQL DB, Excel, SharePoint, and even with Jira, using this connector to obtain specific data from projects.

  4. AI-driven custom reports: Exploring data based on Power BI's Artificial Intelligence (AI) capabilities save time finding patterns and predicting results easily. This activity doesn't require coding and allows using a library containing hundreds of visual elements and customization capabilities using Power BI's open-source code.

  5. Connection with Microsoft Office suite: Another benefit brought by Power BI is to connect with tools like Excel, Word, and others from the Microsoft suite. This allows you to dive deeper into the data and better control the model processing using the DAX formula language. Yes, the same one is used by other Microsoft tools

What's Tableau?

Tableau was born as a project founded in 2003. A group of computer scientists from Stanford University created this tool to help people within an organization to make decisions based on data relevant to their business through visual analysis features.What's Tableau?

Followed by Power BI, Tableau is positioned second as a leader in the Gartner® Magic Quadrant™ for Business Intelligence and Analytics products.
In this study, Tableau stands out as an easy-to-use tool, its customization properties, and the possibility of native integration with Salesforce and other tools, such as Jira, using special connectors to obtain project information. A relevant feature for business teams when creating reports.

Tableau benefits

As a leading option in the BI and Analytics platforms market, Tableau stands out because it facilitates the exploratory process and data management, streamlining the information visualization and sharing process. That's why we list below the main advantages of this tool:

  1. Connection with other tools: It's possible to feed Tableau with data from other tools, either natively (Excel, Google products, and more) or using Jira connectors (for example, to extract project data from Jira with items such as dates, project leaders, status, and more).
    The Artificial Intelligence and Machine Learning features Tableau provides perform different types of analysis, encouraging full end-to-end governance, data management, visual storytelling, and a tight collaboration process.

  2. Intuitive: Data analysis should provide answers to complex questions (business, in this case), that's Tableau's philosophy, and that's why its platform offers several features (depending on the plan, features, and deployment) that allow you to establish a simple data management strategy, without neglecting the process of cleaning, modeling, and visualization of data in a simple way.

  3. Tailor-made visualization: The tool offers "analytics for everyone," allowing to create reports easily and presenting the information contextually (For example, it's possible to represent on a geographical map the sales by state, region, state, etc.).

  4. Tableau Community: Similar to what Atlassian has built, concentrating thousands of people interested in their tools in one place, Tableau has created a hub where more than one million people from around the world share their stories, doubts, problems, hackathons, and day-to-day situations. A community is practically indispensable in answering any question about specific use cases.

The importance of creating a data culture within your organization

Becoming a data-driven organization requires investments in data culture and technology to change how people make decisions. This includes fostering automatic and controlled learning from people and tools, statistics, natural language, and intelligent data preparation. Working consciously on each of these aspects will allow your organization to increase human creativity when performing analysis and optimizing different business areas within your organization. This makes an organization "data-driven," and only 8% of those organizations successfully achieve the goal nowadays.

The world of data is vast, and there are as many situations, processes, transactions, and other measurables coexisting. In this article, we've shown the leading tools and critical concepts you should know when undertaking an improvement in an organization's BI, enabling it by integrating it with other tools source of data for businesses.

If you need further guidance in extracting data from projects in Jira and visualizing it in Power BI or Tableau, check this blog post and pass by the Atlassian Marketplace to find the solution best suits you. Especially the connectors Appfire recently announced: the Power BI Jira Connector and the Tableau Connector Pro for Jira that allow you to extract information from Projectrak project data and transform it into smart decisions for your organization based on Power BI or Tableau analytics. If you have any further questions, please get in touch with us.

Learn how to enhance your project reporting in Jira

Enrich project reporting in Jira

Establishing a data management culture within an organization is necessary for the conscientious optimization and improvement of different areas and departments of the company from a business standpoint.

If you're working with Jira and looking to improve your reports for Jira, click below and learn how to improve project reporting in your instance.

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