What is Software Testing Life Cycle (popular)?
Hive or Apache Hive is the database software that allows you to read, write, and manage large sets of data that are stored in a distributed storage platform using SQL. In this Hive Interview Questions blog, our goal is to cover all the questions that are usually asked by recruiters during any Hive job interview.
The Hive Interview Questions blog is largely divided into the below three parts:
1. Basic
2. Intermediate
3. Advanced
The very first step of any data-centric process is to figure out the right data and get it ready for performing analysis. Obviously, this data will be spread across different sources and to be able to process it there is a need to have a centralized singular source. That’s where the process of Data Ingestion comes into play. With data ingestion, the data stored in different file formats, over different sources, is gathered, sanitized, and transformed into a uniform format.
Want to build a deep understanding of the term Data Ingestion? Keep reading this comprehensive blog on ‘What is Data Ingestion’ to learn this critical component of the data life cycle.
Batch Processing
In batch ingestion, the data from various sources is collected, grouped, and sent in batches to storage locations like a data warehouse or a cloud storage system. The transfer is done based on schedules or when certain conditions are satisfied. This type of ingestion is less expensive compared to other forms of data ingestion.
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For example, a company that handles sales can use batch processing to set up a schedule that sends the sales and inventory reports to the company daily. The image below depicts a simple illustration of Batch Processing:
Batch Processing Architecture
Real-time ingestion is also known as stream processing. In this type of ingestion, there is no grouping
of data; rather, the data is transferred as individual events or messages in real time. Then, new data is received, and it is immediately sent to the storage location. This is usually implemented by using a solution known as change data capture (CDC). This type of ingestion is more expensive as the system needs to monitor the sources for change. The snapshot highlighted below represents the Real-time
data ingestion framework:
Table of content
Data ingestion is a process of gathering data stored in different file formats, across different sources to one single source to carry out the data analysis. This is the first step of data analytics workflow and it is quite important because this is where you comprehend what kind of data your problem statement demands. Generally, companies gather data from various sources, such as websites, social media, Salesforce CRM systems, financial systems, Internet of Things (IoT) models, etc. Typically, data scientists take on this task because this task demands deep knowledge of machine learning alongside programming skills in Python or R programming language. Unlock the potential of data analysis. Join our Data Analytics Course today and gain the skills to make data-driven decisions.1Why is Data Ingestion Important?
Data ingestion is critical considering that it is the first step of any analytics workflow. Not only that, if you ponder upon the importance of getting the right data to solve an analytics problem, you will be able to comprehend the purpose of data ingestion. With this process, you figure out what kind of data is needed by the target environment, how the environment will use that information once it arrives, etc. Below are some more factors that make the data ingestion process highly important:1. Enhances Data Quality1
Data ingestion is critical when it comes to enhancing the quality of data. While setting up the data environment lot of validation checks can be set to ensure the consistency and accuracy of the data. Tasks like data cleaning, standardization, or normalization of data are generally attained in this step, making sure that data is readily analyzable.2. Provides High Flexibility q
By gathering data from a multitude of sources businesses attain the possibility of comprehensively understanding their operations, market trends, and customer base. Once the data ingestion process is set up businesses don’t have to worry about data sources, volumes, and velocity.3. Reduces the Complexity of Analysis Process
Data ingestion makes it easier for companies to analyze the data, as it is transformed into a unified format. By ensuring that the right data is gathered at the target data environment, the unnecessary data variables are mostly omitted, leading to ease in exploratory data analysis.Types of Data Ingestion
Data ingestion can be classified based on how the data is extracted. The three types of data ingestion are mentioned below:
Batch Processing
In batch ingestion, the data from various sources is collected, grouped, and sent in batches to storage locations like a data warehouse or a cloud storage system. The transfer is done based on schedules or when certain conditions are satisfied. This type of ingestion is less expensive compared to other forms of data ingestion.
[videothumb id="veGefarHLYk" title="hello" vidsdes="9"]
For example, a company that handles sales can use batch processing to set up a schedule that sends the sales and inventory reports to the company daily. The image below depicts a simple illustration of Batch Processing:
Batch Processing Architecture
Real-time ingestion is also known as stream processing. In this type of ingestion, there is no grouping
of data; rather, the data is transferred as individual events or messages in real time. Then, new data is received, and it is immediately sent to the storage location. This is usually implemented by using a solution known as change data capture (CDC). This type of ingestion is more expensive as the system needs to monitor the sources for change. The snapshot highlighted below represents the Real-time
data ingestion framework:
Real-Time Data Ingestion Architecture
For example, let’s think of the stock markets. An analyst or a stock trader works on the real-time rates of the stocks. To implement this, real-time ingestion can be used to update the prices of the stocks whenever a change occurs in the prices. Are you interested in learning data science skills? Check the Data Analytics course in Pune Now!Lambda-Based Data Ingestion
Lambda-based data ingestion is a hybrid approach to data ingestion as it uses both batch processing and real-time ingestion, where batch processing is used to gather the data into groups and real-time ingestion is used for time-sensitive data. [newsletter] There are three layers in lambda-based data ingestion:- Batch Layer: This layer is responsible for batch processing.
- Speed Layer: This layer handles the real-time processing.
- Serving Layer: This layer is responsible for responding to queries.
