What is data transformation? What are the benefits of data transformation? What are the processes? Learn all this and more! The last few decades have seen a renaissance in data collection and processing— today’s data teams have more information at their disposal than ever before. While this has led to a proliferation of data analytics & science, it’s presented a number of problems for engineers and business teams. Raw data can be challenging to work with and difficult to filter. Often, the problem isn’t how to collect more data, but which data to store and analyze. To curate
appropriate, meaningful data and make it usable across multiple systems, businesses must leverage data transformation. Data transformation is the mutation of data characteristics to improve access or storage. Transformation may occur on the format, structure, or values of data. With regard to data analytics, transformation usually occurs after data is extracted or loaded
(ETL/ELT). Data transformation increases the efficiency of analytic processes and enables data-driven decisions. Raw data is often difficult to analyze and too vast in quantity to derive meaningful insight, hence the need for clean,
usable data. During the transformation process, an analyst or engineer will determine the data structure. The most common types of data transformation are: In addition, a practitioner might also perform data mapping and store data within theappropriate database technology. What is Data Preparation? | Zuar This article discusses what data preparation entails and how it is done. Zuar | BlogTeam Zuar The Data Transformation ProcessIn a cloud data warehouse, the data transformation process most typically takes the form of ELT (Extract Load Transform) or ETL (Extract Transform Load). With cloud storage costs becoming cheaper by the year, many teams opt for ELT— the difference being that all data is loaded in cloud storage, then transformed and added to a warehouse. The transformation process generally follows 6 stages:
These steps are meant to illustrate patterns of data transformation— no single “correct” transformation process exists. The right process is the one that works for your data team. That is to say, other bespoke operations might occur in a transformation. For example, analysts may filter data by loading certain columns. Alternatively, they might enrich the data with names, geo-properties, etc. or dedupe and join data from multiple sources. Want to automate your ETL processes to enable all of your data to flow into a single destination? Learn more about Zuar’s Mitto platform that allows you to transform, model, report, and manage your data more effectively. Data Transformation TypesThere are two common approaches to data transformation in the cloud: scripting-/code-based tools and low-/no-code tools. Scripting tools are the de-facto standard, with the greatest amount of customization, flexibility, and control over how data is transformed. Nonetheless, low-code solutions have come a long way, specifically in the last few years. We’ll briefly discuss both options. Scripting ToolsThe most common data transformations occur using SQL or Python. At the simplest, these transformations might be stored in a repository and executed using some orchestrator. More commonly, platforms like dbt are used to orchestrate and order transformations using a combination of SQL/Python. These tools or systems often boil down to programmatically creating tables or transformations using some scripting language. The Python Mitto SDK is also useful for scripting and automation. Enabling remote interactions with schedules, jobs, and business functions has never been easier. Want to see Mitto in action? Schedule a demo of the Python Mitto SDK. Low-/No-Code ToolsThese tools are the easiest for non-technical users to utilize. They allow you to collect data from any cloud source and load it into your data warehouse using an interactive GUI. Over the past decade, many low-code solutions have proliferated. Zuar's Mitto is an example of a product that has ETL/ELT capabilities, but also helps you manage data at every step in its journey. Mitto can be hosted either on-premise or in the cloud and has code and no code options. Data Cleaning: Benefits, Steps & Using Clean Data | Zuar This article discusses data cleaning, its benefits, and how to create and use clean data. Zuar | BlogTeam Zuar Data Transformation TechniquesThere are several data transformation techniques that can help structure and clean up the data before analysis or storage in a data warehouse. Here are some of the more common methods:
Data Transformation: BenefitsTransforming data can help businesses in a variety of ways. Here are some of the biggest benefits:
While the methods of data transformation come with numerous benefits, it’s important to understand that a few potential drawbacks exist.
Nonetheless, data transformation is an essential part of any data driven organization. Implementing tests and following the best-practices of software development will help to minimize errors and improve confidence in data. Without experienced data analysts with the right subject matter expertise, problems may occur during the data transformation process. While the benefits of data transformation outweigh the drawbacks, it's necessary to take appropriate caution to ensure sound transformation. Data Transformation ImplementationOrganizing, transforming, and structuring data can be an overwhelming task for many organizations, but with the right research and planning it's possible to integrate a data-driven culture into your business. But first, it’s crucial to have a long-term strategy for analysis and transformation. Zuar offers several products (e.g. our data pipeline tool Mitto) and services that can enable more efficient and accurate data management, by automating many steps in the process! Next Steps: Learn about...
What is Data Integration? | Zuar Data integration systems bundle together your data from all of your different programs into cohesive information that helps your business intelligence. Zuar | BlogTeam Zuar Everything You Need To Know About Data Mapping | Zuar Employ data mapping to combine/migrate all of your desperate data into a single destination. Learn how! Zuar | BlogTeam Zuar Database Migration: What to Know | Zuar Database migration is a decision most businesses will need to make at somepoint. Before the advent of the internet, firms traditionally kept their datapipelines and storage in-house, centralized within their local area networks(LAN). This system was simple, efficient, and allowed companies to fun… Zuar | BlogTeam Zuar What refers to data in an unreadable form?Encryption is the process of transforming information (referred to as plaintext) using an algorithm (called a cipher) to make it unreadable to anyone except those possessing special knowledge, usually referred to as a key. Data can be encrypted in two ways: at rest and in transit.
Is the process of transforming encrypted data into a readable form?Definition: The conversion of encrypted data into its original form is called Decryption.
What is the process of scrambling data to make it unreadable?Encryption is the process of scrambling data to make it unreadable to anyone who does not possess the proper key to unscramble it.
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