Each and every step of ask, prepare, process, analyse, share and act is important for a successful Data Analysis project. Knowingly or unknowingly everybody will be going through each of these processes while doing a Data Analysis project.
ASK
The ASK phase is where the data analyst will ask and find how, why and what is the need of the Data Analysis project. This is the phase where the Data Analyst decides on how the project should go forward, what are the questions to be asked, and how the questions are to be asked.
Prepare
In the PREPARE phase is where data is collected. You need to decide how the data is collected. How secure the data needs to be collected. This is the phase where the data is collected externally or internally is decided. This phase is where the metrics of data collection is decided.
Process
The PROCESS phase is where the data collected is consolidated from various sources. The collected data if necessary is cleaned in this phase using different tools. This phase is where the data is made meaningful for the data analysis project.
ANALYSE
The ANALYSE phase is where the data is analysed to find patterns, trends and relationships between the data to find answers to questions to help solve the problems of the stakeholder accurately. This phase is where the data is made sensible for the stakeholder and finds what solution the data provides.
SHARE
The SHARE phase is where the data is shared with the stakeholder after sharing with subject matter experts who may tweak or add their feedback in the analysed data. This phase is where the data is converted to graphs, charts and plots to convey the analysed data to make more sense to the stakeholder.
ACT
The ACT phase where the analysed data is put into use. Based on the result of the data analysed the stakeholder may or may not act on the problem for a solution. This phase is where the data analysis will help stakeholders to make a good and informed decision.
#DataAnalysis #DataScience #BigData #Analytics #DataManagement #BusinessIntelligence #DataDriven #TechTrends #DataPreparation #DataProcessing #DataVisualization #DataInsights
No comments:
Post a Comment