Data Analytics And The Six Phases

Data Analytics And The Six Phases

Data analysts and detectives have a lot in common. To make decisions, both rely on facts and cues. Both gather and examine evidence. Both speak with persons who are aware of a portion of the narrative. Both may even decide to follow some footsteps to see where they go. Whether you're a detective or a data analyst, your job entails following procedures to gather and comprehend information.

Data-driven decision-making is used by analysts, who follow a step-by-step procedure. This procedure is broken down into six steps, as you've discovered:


1. (ASK) Identify the problem by asking questions and defining it.
2. (PREPARE) Gather and store data in order to prepare data.
3. (PROCESS) Cleanse and double-check the information before processing it.
4. (ANALYZE) Examine data for patterns, connections, and trends.
5. (SHARE) Make data available to your audience.
6. (ACT) Take action based on the data and the findings of the analysis.

What is Big Data Analytics and Why it is so Important? | by Harshali Patel  | Medium

source: Medium

Wisdom when making a decision

Data is at the heart of data-driven decision making. As a result, data analysts must concentrate on the data in order to make informed conclusions. Your decisions may be prejudiced if you overlook data in favor of making conclusions based on your personal experience. Even worse, decisions based solely on intuition without supporting evidence might lead to errors.
Consider a real estate developer who is proposing to redevelop a section of a city's central quarter. They were notable for preserving old structures. To garner support and permission for the project, the agency's planners went with their gut and included the preservation of numerous structures, relying on their reputation.However, private donations fell short, and a partnership that was supposed to save the day never materialized. After significant delay and an expensive legal battle with the city, the structures were eventually demolished.
The more you know about a project's data, the easier it will be to figure out what's needed. These efforts will also assist you in identifying mistakes and gaps in your data, allowing you to better articulate your findings. Past experience might sometimes assist you in making a connection that no one else would perceive. A detective, for example, might be able to solve a case because they recall a past case that's similar to the one they're working on now. It's not only a matter of intuition.



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