Before analyzing data aggregated from multiple sources, it is essential to first standardize the datasets. At PromptCloud, we put special emphasis on this process and understand that as a web crawling company, our solution must enable our clients to integrate data efficiently.
2. What is Data
Standardization?
The process of modifying or transforming data into a consistent format
is called as data standardization.
When you aggregate data from different sources, they are often in
different formats, and to analyse such data it is very important to first
ensure that it is in a consistent format.
Additionally, data standardization may also be required in cases where
the data is only from single source, this is because it may not be
formatted correctly for analysis.
Although this is essential, but it is often done manually and is very time
consuming process. To speed up the process of data standardization,
data analysts use formulas or algorithms. However, it still consumes
time to make sure that the data is ready for analysis.
3. How is data standardization different Normalization?
DATA NORMALIZATION INVOLVES REDUCING
REDUNDANT DATA TO IMPROVE THE DATA INTEGRITY
WHILE DATA STANDARDIZATION IS TO TRANSFORM
DATA IN A STANDARD OR CONSISTENT FORMAT.
ALSO, DATA NORMALIZATION USES A SET OF RULES
TO ORGANIZES THE DATA INTO COLUMNS AND
TABLES. THIS ENSURES THAT THE DATABASE’S
DEPENDENCIES ARE ENFORCED BY INTEGRITY
CONSTRAINTS.
DATA NORMALIZATION IS A WAY TO ORGANIZE A
DATABASE INTO TABLES WHEREAS DATA
STANDARDIZATION HELPS TO REFORMAT THE DATA
FOR ANALYSIS.
4. What is the need
for Data
Standardization?
Customer sentiment analysis,
competitive analysis and market
research often need to analyse the
data from multiple sources. Therefore,
in order to analyse all the data, it is
crucial that it is in a consistent format.
Corporations often make data driven
business decisions for which they
must have reliable data.
The data quality is dependent on the
data standardization, if the datasets
are merged without standardization
then it can lead to decisions based on
false data. For example: eCommerce
companies do the competitor analysis
and market research based on the
standardized data.
6. Data
Standardization
with Web Data
Integration
Integrating web data manually or using traditional
web scraping methods involves higher risks and
costs because of challenges like incomplete,
inaccurate, unreliable and out of date data.
7. Data
Standardization
with Web Data
Integration
Web Data Integration provides high quality,
extensive data which is ready for analysis.
Therefore, organizations can get data from
anywhere and analyze it instantly by using Web
Data Integration.
8. Data
Standardization
with Web Data
Integration
To get an edge over competitors in this
dynamic market, businesses are making more
and more data driven decisions. For example:
online travel booking services, ecommerce,
banking services, have been trying to provide
all the services a customer may need and hence
the competition has become fiercer in every
industry
10. Web Data
Integration by
Promptcloud
Most common use of web data for ecommerce
Our Web Data Integration solution includes
extracting, cleaning, integrating and consuming
data through data standardization process. This
can provide your business the required reliable
data in the required format within minutes and
hence save the ordeal of spending time and
valuable resources on getting the accurate data.
11. Web Data
Integration by
Promptcloud
Web Data gives your business such valuable
insights which enables you to enhance your
brand and improve customer loyalty by meeting
customer needs.
12. Web Data
Integration by
Promptcloud
Our Web Data Integration solution includes
extracting, cleaning, integrating and consuming
data through data standardization process. This
can provide your business the required reliable
data in the required format within minutes and
hence save the ordeal of spending time and
valuable resources on getting the accurate data.