Task sheet 2 - Paraphrasing - Bussiness (BUS123) | Đại học Hoa Sen

Task sheet 2 - Paraphrasing - Bussiness (BUS123) | Đại học Hoa Sen được sưu tầm và soạn thảo dưới dạng file PDF để gửi tới các bạn sinh viên cùng tham khảo, ôn tập đầy đủ kiến thức, chuẩn bị cho các buổi học thật tốt. Mời bạn đọc đón xem

18 9 lượt tải Tải xuống
Chia sẻ Báo cáo tài liệu

Môn: Bussiness (BUS123)

Trường: Đại học Hoa Sen

Thông tin:

108 trang 4 tuần trước

Tác giả:

Profile Kim Oanh
Business Decision Making
Module 2: Data & Assessment Tools
Week 5: Data Insights
Extracting insights
from data
2
RMIT Classification: Trusted
Overview
• In this topic, we will explore how to extract
insights from data to aid decision-making
• You will learn how to:
• extract data insights from data
• use data visualisation techniques
• create powerful reports that effectively
communicate data insights through
visualisations and inform sound business
decision making
RMIT Classification: Trusted
Activities
By the end of this topic, you’ll be able to:
• understand what makes a good report
• apply descriptive statistics to help analyse
and communicate
• enhance the communication of results by
applying visualisation of data
• demonstrate the role of infographics and
dashboards in the decision making process
RMIT Classification: Trusted
Extracting insights
from data
• Extracting the right insights from
data is important for effective
business decision-making
• In this video, we explore how to
prepare data and generate insights
Preparing data
• Data downloaded from a database is often not ready
for analysis
• Data preparation process of cleaning and is the
transforming a raw dataset to make it ready for
analysis
• Crucial step that, if overlooked, can result in
nonsensical analysis or, worse, incorrect analysis
• Can be a time-consuming task!
Data preparation methods
• Filtering: Focusing only on a subset of data from a large
dataset
• Validation: Ensuring data is reported in a consistent and
“expected” manner
• Shaping: Consolidation and transformation of the
structure of the data
• Joining: Combination of different datasets based on a
relationship
• Deletion: Deletion of data that is either a duplicate or an
error
• Aggregation: Summarisation of data into descriptive
statistic measures
Data insights
• Data insights:
• start from raw data that has been cleansed, interrogated
and prepared for analysis
• refers to identifying patterns or relationships in data
that may not have previously been known
• A will use a range of quantitative and data analyst
qualitative techniques to “ ” from a data settell a story
• Data insights can be used to:
• draw conclusions which are applied to a business problem
• generate powerful reports and dashboards
Generating insights
Insights can be generated via several different methods
including:
• descriptive statistics
• data visualisations
• predictive modelling (such as regression analysis)
• data optimisation
• outlier identification
• key performance indicator (KPI) generation
In the next video, we explore descriptive statistics as an
example of how this can be used to generate insights
Leveraging descriptive
statistics
10
| 1/108
| | Tải xuống

Có thể bạn quan tâm:

Preview text:

Business Decision Making
Module 2: Data & Assessment Tools Week 5: Data Insights Extracting insights from data 2 RMIT Classification: Trusted Overview
• In this topic, we will explore how to extract
insights from data to aid decision-making • You will learn how to:
• extract data insights from data
• use data visualisation techniques
• create powerful reports that effectively
communicate data insights through
visualisations and inform sound business decision making RMIT Classification: Trusted Activities
By the end of this topic, you’ll be able to:
• understand what makes a good report
• apply descriptive statistics to help analyse and communicate
• enhance the communication of results by
applying visualisation of data
• demonstrate the role of infographics and
dashboards in the decision making process RMIT Classification: Trusted Extracting insights from data •
Extracting the right insights from
data is important for effective business decision-making •
In this video, we explore how to
prepare data and generate insights Preparing data
• Data downloaded from a database is often not ready for analysis
• Data preparation is the process of cleaning and
transforming a raw dataset to make it ready for analysis
• Crucial step that, if overlooked, can result in
nonsensical analysis or, worse, incorrect analysis
• Can be a time-consuming task! Data preparation methods
• Filtering: Focusing only on a subset of data from a large dataset
• Validation: Ensuring data is reported in a consistent and “expected” manner
• Shaping: Consolidation and transformation of the structure of the data
• Joining: Combination of different datasets based on a relationship
• Deletion: Deletion of data that is either a duplicate or an error
• Aggregation: Summarisation of data into descriptive statistic measures Data insights • Data insights:
• start from raw data that has been cleansed, interrogated and prepared for analysis
• refers to identifying patterns or relationships in data
that may not have previously been known
• A data analyst will use a range of quantitative and
qualitative techniques to “tell a story” from a data set
• Data insights can be used to:
• draw conclusions which are applied to a business problem
• generate powerful reports and dashboards Generating insights
Insights can be generated via several different methods including: • descriptive statistics • data visualisations
• predictive modelling (such as regression analysis) • data optimisation • outlier identification
• key performance indicator (KPI) generation
In the next video, we explore descriptive statistics as an
example of how this can be used to generate insights Leveraging descriptive statistics 10