Blog Writing Report: Data Transformation, Challenges, and Solutions

This report delves into the critical role of data transformation in blog writing and data analysis. It begins by defining data transformation as the systematic conversion of data from one format to another, essential for researchers and analysts to interpret collected data effectively. The report outlines the data transformation process, including data discovery, mapping, code generation, execution, and review. It distinguishes between batch and interactive data transformation, detailing their methodologies and applications. The report emphasizes the reasons for data transformation, such as data migration, integration of structured and unstructured data, and data enrichment. It highlights the benefits of data transformation, including improved data quality, error reduction, faster query times, and better data organization. Additionally, the report explores various transformation methods like scripting, on-premise, and cloud-based ETL tools, and discusses the challenges associated with data transformation, such as time consumption and high costs. Finally, the report introduces Alooma as a cloud-based ETL solution that simplifies data transformation, offering support, cost-effectiveness, and speed to streamline the process.

Running head: Blog writing
BLOG WRITING

Running head: Blog writing
DATA TRANSFORMATION
July 25th, 2019
INTRODUCTION TO THE DATA TRANSFORMATION
In the field of computing, the concept such as data transformation tends to play a vital
role. However, the given transformation is mainly useful for the researchers that are planning to
make an analysis of the collected data. In this regard, it is examined that in order to interpret the
result of the collected data, the researcher has to transform the data in some specific format
which is readable to his/her system or the software. If it is not done then in this situation a
researcher is not able to attain its goals and objectives in an effectual way.
Thus, it can be said that data transformation is being regarded as the systematic process
of converting the data from one format to another. It is being regarded as one of the most
fundamental aspects of the concept such as data integration. Data integration is the process of
combining the data that are being resided in the different sources and it will also provide the user
the unified view of the data in an effectual way.
On the other hand, it can also be said that there is a different type of activities are
involved in the concept such as data transformation. It comprises converting the types of data,
to perform the cleaning of the data by removing different duplicate and the null data, to enrich
the data and to carry out the aggregations, etc. Besides this, there are some benefits are also
associated with the data transformation. However, discussion about the same is carried out
later.
DATA TRANSFORMATION PROCESS
In order to get more details about the concept such as data transformation, it is very
much important for the individual that it should have a thorough understanding about the process
which is being used for data transformation. The details about the same are depicted below:
 Data discovery: The process of the data transformation begins with the discovery of
data. In accordance with the given context, it can be said that in the respective phase
mainly profiling of the data is performed. However, with an aim to do the same
assistance is being taken from different profiling tools in an effectual way. Among all,
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basically, the written profiling script is being used in this. This is used with an aim to get
a better idea about the characteristics and structure of data.
 Data mapping: In the second step, it is being defined that how different individual field
can be mapped, joined, modified, aggregated and fitted together. This is done with an aim
to perform the production of the final desired output. The mapping of data is being done
by the developer from the time when they start working on the specific type of
technology.
 Code generation: It is being regarded as the third step of data transformation. Herein,
different executable code is being generated that will help in the process of transforming
the data as per the desired data mapping rules. Typically, different data transformation
technologies are used here in order to generate the code.
 Code execution: In the respective step, the code which is generated above is sent for the
execution purpose. The codes which are executed are being integrated into the
transformation tool.
 Data review: It is the final step in which programmer or the analyst will get the idea that
whether the output of the data is fulfilling all the requirements of data transformation or
not.
TYPE OF DATA TRANSFORMATION
Till now we have gathered much more information about the data transformation. Now
we will discuss more about the different types of data transformation. In this context, the
details about the same are given below:
The data transformations are of two types such as batch data transformation and the
interactive data transformation.
Batch data transformation
Traditionally, the activity of the data transformation is being performed in the bulk or
in the batch. In this regard, in the respective form of data transformation, the developers used
to write the code and they also used to perform the implementation of different transformation
rules in the data integration tools in an effectual way. After doing the same, they perform the
execution of the generated code on the large volume of the data. The respective process tends to
follow the linear set of steps. In other words, it can also be depicted that batch data
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transformation is being regarded as the cornerstone of different type of data integration
technologies that comprise of data warehousing, application integration, and the data migration.
Interactive data transformation
It is being regarded as another type of data transformation. It is the type of emerging
capability that tends to allow business users and analyst to perform direct interaction with the
large dataset with the help of the visual interface. Here, the features of data are understood and
data is also corrected with the use of simple interactions. However, it can be said that the
respective type of data transformation also follows a similar type of data integration step which
is being followed by the batch data transformation. But, in interactive data transformation, it is
not necessary to comply with the linear fashion which is done in batch data transformation in an
effectual manner.
REASON FOR TRANSFORMING THE DATA
There are some major reasons examined which lead to the activity such as data
transformation.
 The need for data transformation tends to arises when an individual will move the data
to the new data store. For instance, when a person will move the data to the cloud data
warehouse than in this situation it needs to change the type of data.
 When data is being moved on to another system or the software.
 This is also performed when unstructured data is being joined with the structured data.
This is done with an aim to perform the data analysis.
 The data transformation will also need to perform when an individual wants to add the
information to data in order to enrich the same. This involves performing the addition of
geolocation data and performing lookups etc.
 The data transformation will also need to perform when aggregation needs to be
performed which involves performing the comparison of sales data from the varied
regions. Therefore it can be said that they are being regarded as the main reason behind
the data transformation.
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BENEFITS OF DATA TRANSFORMATION
Now discussion will be carried out on the main benefits that are associated with the
concept of data transformation. The detail explanations about the same are given below:
 Higher data quality: It is being regarded as a very first benefit that is related to data
transformation. This happens because here an individual will tends to convert its data in
a high-quality format.
 It also helps in reducing the number of mistakes: While writing the data, an individual
sometimes do various types of mistakes such as duplication of data and missing values,
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etc. thus, with the help of data transformation such mistakes can be detected and
significant actions can be taken with an aim to resolve the same.
 It also assists in the task of making the query time much faster and it also enhances the
retrieval time also.
 In this very minimal resources are needed for the purpose to perform the manipulation of
the data in an effectual way.
 It also helps in the task of performing better and the effective organization of the data.
 The data here are more usable in a case like business intelligence. Thus, these are some
major benefits that are related to the concept such as data transformation in an effectual
way.
WAYS TO TRANSFORM THE DATA
There are three major ways with the help of which the data can be transformed. These
are:
 Scripting: One of a way to transform data is scripting. There are many companies that
tend to perform the data transformation with the help of scripting. However, for the given
purpose they tend to use means like SQL and Python. These techniques are used to write
the code and perform the extraction of data. It is through this way only data
transformation is done.
 On-premise ETL tools: Here, ETL (Extract, Transform and Load) tools are being used in
order to take much of the pain out of scripting the transformation. The given tools are
majorly hosted from the site of the company. On the other hand, they require
infrastructure cost as well as extensive expertise.
 Cloud-based ETL tools: The respective tools are being hosted on the cloud, this will
allow an individual to leverage infrastructure as well as expertise of the vendor in an
effectual way. Hence, these are some main ways with the help of data transformation is
being performed by the individual. It is through this way the only individual can convert
data as per his/her desire.
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CHALLENGES ASSOCIATED WITH THE DATA TRANSFORMATION
There are different types of challenges are related to the concept such as data
transformation.
 It is very much time-consuming in nature: The very first challenge that an individual will
encounter from the data transformation is time-consuming. Here, before starting the
data transformation the programmer will have to clean extensive data. It needs to assure
here that no other data should remain during the data transformation process in an
effectual way. The given thing is very much time-consuming in nature. On the other
hand, it is being regarded as one of the most common complaints that always comes from
the side of a data scientist in an effectual manner.
 It is very costly in nature: The second most significant challenge that is related to data
transformation is that it is very much costly in nature. Here, it almost depends on the
infrastructure. On the other hand, the process to transform the data requires highly
specialized and skilled people. This is because; in order to do the data transformation
work an individual should be good technical knowledge. Further, it also involves
infrastructure costs also. It raises the overall time of doing the respective function
 It is very slow: The activity such as data transformation as well as data extraction puts
very much burden on the system of the computer. Thus, it is due to the presence of a
given aspect it is often performed in the batches. This means that a programmer will need
to wait for 24 hours with an aim to see the processing of its next batch. The given thing
will cost the firm in time in the process of make the business decision. Overall, it is very
correct to say that by taking significant actions in relation to these challenges the whole
activity of data transformation can be made much easier and effective.
USEFULNESS OF ALOOMA IN DATA TRANSFORMATION
Alooma is basically the cloud-based ETL solution that assists in easing the difficulties
that are related to the data transformation. Herein, it can be said that Alooma has a very
important role in data transformation. However, all the details about the same are explained
below:
 Support: The very first thing that Alooma performs is to give support to the whole
process of data transformation. In this context, it can be depicted that Alooma
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possesses the team of expert individuals that assist individuals in the task of expediting
the whole process of the data transformation. It involves the process of planning the
data mapping to the transformation of data. Finally, in the end, the results are verified.
 Cost-effective; It is cost-effective in nature because here an individual can leverage
Alooma’s expert. This is due to the reason that the respective software is cloud-based.
Hence, by using Alooma firm can avoid the maintenance of infrastructure as well as it
can also avoid the payment to the team of experts. Thus, the money which is being saved
from the given purpose can be used for some other effective purposes in an effectual way.
 Fast: It has been examined that the software such as Alooma can transform, load and
extract the data in real-time. Thus, an individual will have enough time in making a
decision about the company. However, it is also assessed that Alooma is also very much
flexible in nature. It is the reason why it tends to make the whole activity of data
transformation very much easier.
 Secure: Alooma assists in removing sensitive information before performing the data
transformation process. Hence, the respective software is very much useful. Thus, it is
very right to say that Alooma is very much useful software for the transformation of the
data.
FAMOUS DATA TRANSFORMATIONAL LANGUAGES
Till now we have gained huge knowledge about the data transformation, now it’s time
to get the details about the languages that are being used in the data transformation. In
accordance with the given context, it can be said that there are a different type of languages
available that perform the function of data transformation. There are many languages that
needed grammar to be provided. There are many situations in which grammar to be structured
with the help of the Backus-Naur Form (BNF). Herein, it can be said that there are many
languages available and the details about the same are given below:
 AWK: It is being regarded as the very first transformational language. On the other hand,
it is being regarded as one of the most oldest as well as the most popular form of textual
data transformational form of language.
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 Perl: It is another type of data transformation language. It is the high-level language
that involves both the object-oriented and procedural syntax. They are very much capable
of doing powerful operation on the text or the binary data in an efficient way.
 Template language: it is very much specialized form of data transformation language. It
tends to transform the data into a specific language.
 TXL: It basically prototypes the language-based description. On the other hand, it is
basically used for the data transformation or the source code.
 XSLT: It is also called by the name of standard XML language. It is very much suitable
for the X query. Overall, it is very right to say that it is with the assistance of these all
given languages only all the data can be transformed into the specific type of format.
CONCLUSION
It can be concluded that the concept such as data transformation is very much useful for
the individuals. In this regard, it can be said that with the help of software like Alooma all the
difficulties that are related to the data transformation can be avoided in an effectual way. On
the other hand, there is a number of benefits are also related to the process of converting data
from one format to another. The given conversion will mainly assist data analyst who used to
take a decision on the basis of collected data.
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