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Last updated on 2024年6月21日

Here's how you can uncover your strengths and weaknesses in data warehousing with feedback.

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Data warehousing is an essential skill for businesses looking to make informed decisions based on large volumes of data. However, like any complex process, it has its challenges. By actively seeking feedback on your data warehousing processes, you can identify what you're doing right and where you might need improvement. This feedback can come from various sources, such as performance metrics, peer reviews, or customer satisfaction surveys. Embracing this feedback is key to refining your data warehousing strategies and ensuring that your data is accurate, accessible, and actionable.

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Carlos Fernando Chicata

Algunas insignias de community Top Voice | Ingeniero de datos | AWS User Group Perú - Arequipa | AWS x3
Philippe Bouvier

Chef de projet BI Senior

1 Gather Feedback

Gathering feedback is the first step in understanding your data warehousing strengths and weaknesses. You can start by reviewing system logs to identify any recurring errors or bottlenecks. Engage with end-users and ask for their input on the data's usability and relevance. Additionally, consider setting up automated alerts to monitor system performance in real-time. This proactive approach will help you catch issues early and adjust your processes accordingly.

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Carlos Fernando Chicata

Algunas insignias de community Top Voice | Ingeniero de datos | AWS User Group Perú - Arequipa | AWS x3
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Classify all feedback that you gather; so you can analyze it and get new knowledge associated it like frequency, impacted users or related area: these points help you to get a context of situation and detect weakness or strengths on your data warehouse. More details on your feedback; better your results and your detection about the data warehouse.

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2 Analyze Data

Once you've collected feedback, it's time to analyze the data. Look for patterns that indicate strengths, such as consistently high performance in data processing speed or user satisfaction with the accessibility of reports. Conversely, pay attention to areas with frequent issues, which may point to weaknesses in your architecture or processes. Use tools like query performance reports to drill down into specifics and understand the root causes of any problems.

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Philippe Bouvier

Chef de projet BI Senior
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Une approche qu'il est indispensable d'implémenter , c'est le controle d'intégrité des données. Les sources de données pouvant être tres heterogenes , il faut mettre en oeuvre des processus qui vous permettront de certifier , à vos utilisateurs, le niveau de fiabilité optimal demande et bien évidemment faire évoluer ceux-ci avec l'enrichissement de vos données.

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3 Peer Review

Peer reviews can be a valuable source of feedback for data warehousing. Arrange for colleagues with data warehousing expertise to review your setup and processes. Their insights can help you see things from a different perspective and identify areas for improvement that you might have overlooked. Peer feedback can also affirm the areas where your practices align with industry standards and best practices.

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4 Customer Insight

Customer feedback is crucial in evaluating the effectiveness of your data warehousing solutions. If the end goal of your data warehouse is to provide insights to customers or internal stakeholders, their satisfaction is a direct reflection of your success. Gather feedback through surveys or direct communication to understand how well your data warehousing serves their needs and what could be improved to enhance their experience.

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Philippe Bouvier

Chef de projet BI Senior
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J'ai notamment constaté qu'il faut rester pragmatique dans ce que l'on propose aux clients car s'il est tentant de faire miroiter des fonctionnalités multiples dès les debuts des projets , il faut gagner la confiance du client des le début et lui montrer l'evolutivite de la solution en l'incluant à chaque étape suivante afin de faire de lui l'ambassadeur de la solution.

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5 Refine Processes

Taking feedback into account, you can start refining your data warehousing processes. This might involve reconfiguring your Extract, Transform, Load (ETL) processes, optimizing indexes, or enhancing data quality checks. It's important to prioritize changes that will have the most significant impact on performance and user satisfaction. Implementing changes in a controlled manner allows you to measure their effectiveness and continue the cycle of improvement.

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6 Continuous Improvement

Continuous improvement is the ultimate goal of feedback in data warehousing. Establishing a culture where feedback is regularly sought, valued, and acted upon will keep your data warehousing practices agile and effective. Encourage ongoing communication between your data team and its stakeholders to maintain a clear vision of what's working well and what needs attention. This iterative process ensures that your data warehouse evolves to meet changing business needs and technological advancements.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Here's how you can uncover your strengths and weaknesses in data warehousing with feedback.

1

2

3

4

5

6

7

1 Gather Feedback

2 Analyze Data

3 Peer Review

4 Customer Insight

5 Refine Processes

6 Continuous Improvement

7 Here’s what else to consider

Data Warehousing

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Here's how you can uncover your strengths and weaknesses in data warehousing with feedback.

1

2

3

4

5

6

7

1 Gather Feedback

2 Analyze Data

3 Peer Review

4 Customer Insight

5 Refine Processes

6 Continuous Improvement

7 Here’s what else to consider

Data Warehousing

给文章评分

感谢您的反馈

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