We’ve seen it used numerous times, from the cover of prominent publications to speeches by Fortune 500 CEOs and world leaders: “data is the new oil”.
For data to create value and economic benefits for the organization, it must pass through various steps from data collection, cleansing, storage, governance, visualization, analysis, and the last and most important step decision making.
Too often organizations will start on data analysis journey, will spend tons of resources on data infrastructure & analysis, but will not go to the last step of making decisions based on data.
Brent Dykes in the article Data analytics marathon has very nicely drawn the parallels of data analysis journey and running the marathon and why the last step is the most critical one.
Here are the steps in data analytics marathon.
1. Data collection. You collect all kinds of raw data on your business operations from different sources. Much of this data will be generated automatically regardless of whether you want it or not. Some of your data may require thought and effort (strategy) to be captured correctly so it can address critical business questions.
2. Data preparation. Before you can use your data, it must be cleansed, combined and formatted for reporting and analysis purposes. Without accurate and consistent data, it’s going to be difficult to obtain valuable insights from what’s collected.
3. Data visualization. To monitor business performance, your data must be visualized in reports and dashboards. By sharing this summarized information throughout your organization, managers and employees will be able to observe how different aspects of the business are performing.
4. Data analysis. To gain deeper insights into the business, your people will need to explore the data for potential issues or opportunities. An iterative process of data discovery will help your organization unlock insights that can lead to enhanced business performance.
5. Insight communication. To ensure the insights drive the right decisions and actions, they must be communicated effectively. Data storytelling opens the audience’s minds to new possibilities, using engaging narratives and clear visuals to explain key insights.
6. Take action. The last crucial step is to decide which insights should be pursued and then implement the necessary changes. In some cases, you may deploy a test first to verify the results before making wholesale alterations. Regardless, you’ll want to assess the results after each change and learn from them.
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Data Analytics Marathon: Why Your Organization Must Focus On The Finish
