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What is the IMPACT Cycle of Data Analytics? 6 Key Steps
- The IMPACT cycle of data analytics is a framework introduced by Jean-Paul Isson and Jesse Harriott to guide data users in turning raw data into actionable insights effectively.
- This cycle consists of six key steps, starting with identifying specific and measurable business questions to be answered.
- Data mastery involves collecting data from various sources, cleaning, and transforming it for analysis.
- Effective data cleaning ensures the accuracy and reliability of insights derived from the data.
- The cycle emphasizes the importance of providing meaning behind the data through analytical techniques and data visualizations.
- Actionable recommendations should be specific, measurable, and directly related to the insights gained from data analysis.
- Communication of insights involves utilizing various methods like interactive dashboards, presentations, and executive memos to convey findings to different stakeholders.
- Tracking outcomes is essential to measure the effectiveness of recommendations and identify areas for improvement.
- The IMPACT cycle helps in understanding data, improving communication, measuring outcomes, enhancing decision-making, and minimizing risks in data analytics.
- Challenges in adopting the cycle include time investment, difficulty in identifying questions, data quality issues, the need for skilled personnel, and measuring long-term impacts.
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