{"id":9670,"date":"2021-05-24T21:29:15","date_gmt":"2021-05-24T15:59:15","guid":{"rendered":"https:\/\/www.h2kinfosys.com\/blog\/?p=9670"},"modified":"2025-11-13T05:35:21","modified_gmt":"2025-11-13T10:35:21","slug":"big-data-testing","status":"publish","type":"post","link":"https:\/\/www.h2kinfosys.com\/blog\/big-data-testing\/","title":{"rendered":"Big Data Testing"},"content":{"rendered":"\n<p>Big data is no longer a buzzword. From healthcare and finance to e-commerce and entertainment, massive volumes of data are now the backbone of decision-making. But with such enormous amounts of structured, semi-structured, and unstructured data flowing through distributed systems, ensuring data accuracy, quality, performance, and reliability has become a critical priority. This is where <strong>Big Data Testing<\/strong> plays a vital role.<\/p>\n\n\n\n<p>For anyone pursuing a <strong><a href=\"https:\/\/www.h2kinfosys.com\/courses\/qa-online-training-course-details\/\">Software testing and quality assurance course<\/a><\/strong> understanding Big Data Testing is essential to becoming a job-ready QA professional. This guide covers everything you need to know concepts, types, tools, challenges, strategies, and real-time examples.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img fetchpriority=\"high\" decoding=\"async\" width=\"890\" height=\"525\" src=\"https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-12.png\" alt=\"\" class=\"wp-image-31985\" title=\"\" srcset=\"https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-12.png 890w, https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-12-300x177.png 300w, https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-12-768x453.png 768w, https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-12-150x88.png 150w\" sizes=\"(max-width: 890px) 100vw, 890px\" \/><\/figure>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Introduction:<\/strong><\/h1>\n\n\n\n<p>We are living in a world where over <strong>328.77 million terabytes of data<\/strong> are created every single day. Organizations rely on advanced analytics, machine learning, and BI <a href=\"https:\/\/en.wikipedia.org\/wiki\/Dashboard\" rel=\"nofollow noopener\" target=\"_blank\">dashboards<\/a> to make informed decisions. But what happens when the data driving these decisions is inaccurate, slow, inconsistent, or corrupt?<\/p>\n\n\n\n<p>The consequences can be serious:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Wrong business insights<\/li>\n\n\n\n<li>Faulty risk predictions<\/li>\n\n\n\n<li>Poor customer experience<\/li>\n\n\n\n<li>Security vulnerabilities<\/li>\n\n\n\n<li>Performance issues under heavy loads<\/li>\n<\/ul>\n\n\n\n<p><strong>Big Data Testing<\/strong> ensures that:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data is accurate<\/li>\n\n\n\n<li>Data processing pipelines function correctly<\/li>\n\n\n\n<li>Systems perform well at scale<\/li>\n\n\n\n<li>Reports and dashboards reflect the truth<\/li>\n\n\n\n<li>Business decisions are reliable<\/li>\n<\/ul>\n\n\n\n<p>As companies increasingly adopt data-driven cultures, the demand for skilled QA testers with big data knowledge is skyrocketing.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>What Is Big Data Testing?<\/strong><\/h1>\n\n\n\n<p>Big Data Testing refers to validating large data sets that cannot be processed using traditional data-handling tools due to their volume, velocity, and variety. It ensures:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data integrity<\/li>\n\n\n\n<li>Data quality<\/li>\n\n\n\n<li>Processing efficiency<\/li>\n\n\n\n<li>Performance under load<\/li>\n\n\n\n<li>Functional accuracy of pipelines<\/li>\n<\/ul>\n\n\n\n<p>Unlike traditional QA, which focuses on small-scale data or application features, Big Data Testing ensures correctness across <strong>massive distributed systems like Hadoop, Spark, Hive, HBase, NoSQL databases, ETL pipelines, and data warehouses<\/strong>.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Key Characteristics of Big Data<\/strong><\/h1>\n\n\n\n<p>Understanding big data begins with the classic <strong>3 Vs<\/strong>, which later expanded to <strong>5 Vs<\/strong>:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. Volume<\/strong><\/h3>\n\n\n\n<p>Huge amounts of data petabytes and exabytes.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2. Velocity<\/strong><\/h3>\n\n\n\n<p>Real-time or near real-time data streaming (IoT, logs, sensors).<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>3. Variety<\/strong><\/h3>\n\n\n\n<p>Data comes in multiple formats text, images, videos, logs, social media feeds, CSV, JSON, XML, spreadsheets, and more.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>4. Veracity<\/strong><\/h3>\n\n\n\n<p>Ensuring data accuracy and trustworthiness.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>5. Value<\/strong><\/h3>\n\n\n\n<p>Extracting meaningful insights that add business value.<\/p>\n\n\n\n<p>Testing must ensure that all these aspects are validated and aligned with business goals.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Types of Big Data Testing<\/strong><\/h1>\n\n\n\n<p>Big Data Testing involves multiple layers and techniques, and a QA engineer must be skilled in all of them.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>1. Data Validation Testing (Pre-Processing Phase)<\/strong><\/h2>\n\n\n\n<p>Before data enters the Hadoop\/Spark ecosystem, QA engineers validate:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Source data correctness<\/li>\n\n\n\n<li>File formats (CSV, XML, JSON, Parquet)<\/li>\n\n\n\n<li>Schema validation<\/li>\n\n\n\n<li>Data mapping<\/li>\n\n\n\n<li>Null, duplicate, or inconsistent values<\/li>\n\n\n\n<li>Referential integrity<\/li>\n<\/ul>\n\n\n\n<p>Example:<br>Ensuring that all transactions from an online banking system are accurately captured before processing begins.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>2. ETL Testing (Extraction, Transformation, Loading)<\/strong><\/h2>\n\n\n\n<p>ETL Testing is central to big data environments.<\/p>\n\n\n\n<p>You validate:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data extraction logic<\/li>\n\n\n\n<li>Transformations (aggregations, joins, filters, cleansing)<\/li>\n\n\n\n<li>Loading into HDFS, HBase, Hive, or a data warehouse<\/li>\n\n\n\n<li>Data completeness<\/li>\n\n\n\n<li>Data correctness<\/li>\n\n\n\n<li>Data duplication checks<\/li>\n<\/ul>\n\n\n\n<p>Example:<br>Testing whether all customer records from multiple CRM systems merge correctly without missing or duplicate data.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>3. Functional Testing of Big Data Applications<\/strong><\/h2>\n\n\n\n<p>This ensures the system behaves as expected. Tasks include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Validating business rules<\/li>\n\n\n\n<li>Checking data workflows<\/li>\n\n\n\n<li>Verifying job triggers and scheduling<\/li>\n\n\n\n<li>Ensuring transformations meet business requirements<\/li>\n<\/ul>\n\n\n\n<p>Tools like Hadoop MapReduce, Spark jobs, and Kafka message streams are validated for accuracy.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>4. Performance &amp; Scalability Testing<\/strong><\/h2>\n\n\n\n<p>Big data systems must handle massive loads and user requests.<\/p>\n\n\n\n<p>QA validates:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>How quickly Hadoop\/Spark jobs run<\/li>\n\n\n\n<li>How efficiently data pipelines scale under load<\/li>\n\n\n\n<li>Query performance (Hive, Presto, Impala)<\/li>\n\n\n\n<li>Capacity planning<\/li>\n\n\n\n<li>Cluster utilization<\/li>\n<\/ul>\n\n\n\n<p>Example:<br>A retail platform analyzing billions of transactions during Black Friday must process data in seconds not hours.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>5. Data Quality Testing<\/strong><\/h2>\n\n\n\n<p>One of the most important aspects.<\/p>\n\n\n\n<p>You evaluate:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Completeness<\/li>\n\n\n\n<li>Consistency<\/li>\n\n\n\n<li>Accuracy<\/li>\n\n\n\n<li>Timeliness<\/li>\n\n\n\n<li>Duplication<\/li>\n\n\n\n<li>Validity<\/li>\n\n\n\n<li>Formatting<\/li>\n<\/ul>\n\n\n\n<p>Example:<br>Validating that no product catalog data is missing in an e-commerce site.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>6. Security Testing<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"1024\" height=\"512\" src=\"https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-13.png\" alt=\"\" class=\"wp-image-31986\" title=\"\" srcset=\"https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-13.png 1024w, https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-13-300x150.png 300w, https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-13-768x384.png 768w, https:\/\/www.h2kinfosys.com\/blog\/wp-content\/uploads\/2021\/05\/image-13-150x75.png 150w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>Data security is mandatory in today\u2019s cybersecurity-focused world.<\/p>\n\n\n\n<p>QA tests:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Authentication &amp; authorization<\/li>\n\n\n\n<li>Data masking<\/li>\n\n\n\n<li>Encryption<\/li>\n\n\n\n<li>User roles<\/li>\n\n\n\n<li>Data access controls<\/li>\n\n\n\n<li>Compliance with GDPR, HIPAA, SOC2<\/li>\n<\/ul>\n\n\n\n<p>Example:<br>Ensuring that personally identifiable information (PII) is encrypted in transit and at rest.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Big Data Testing Architecture<\/strong><\/h1>\n\n\n\n<p>A typical big data testing architecture includes the following components:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Data Sources<\/strong> \u2013 ERP, CRM, logs, sensors, social media, finance systems<\/li>\n\n\n\n<li><strong>Ingestion Layer<\/strong> \u2013 Kafka, Flume, Sqoop<\/li>\n\n\n\n<li><strong>Distributed Storage<\/strong> \u2013 HDFS, NoSQL, cloud storage<\/li>\n\n\n\n<li><strong>Processing Layer<\/strong> \u2013 Hadoop MapReduce, Spark, Hive, Pig<\/li>\n\n\n\n<li><strong>Data Warehouse<\/strong> \u2013 Snowflake, Redshift, BigQuery<\/li>\n\n\n\n<li><strong>Visualization Layer<\/strong> \u2013 Tableau, Power BI, Qlik<\/li>\n\n\n\n<li><strong>QA Tools<\/strong> \u2013 JMeter, Selenium, Talend, Informatica, QuerySurge<\/li>\n<\/ol>\n\n\n\n<p>Understanding these components prepares you for any big data project.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Key Tools Used in Big Data Testing<\/strong><\/h1>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. Hadoop Ecosystem Tools<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>HDFS<\/li>\n\n\n\n<li>MapReduce<\/li>\n\n\n\n<li>Hive<\/li>\n\n\n\n<li>Pig<\/li>\n\n\n\n<li>HBase<\/li>\n\n\n\n<li>YARN<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2. Spark Ecosystem<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>PySpark<\/li>\n\n\n\n<li>SparkSQL<\/li>\n\n\n\n<li>Spark Streaming<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>3. Data Ingestion Tools<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Kafka<\/li>\n\n\n\n<li>Flume<\/li>\n\n\n\n<li>Sqoop<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>4. Data Quality Tools<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Talend<\/li>\n\n\n\n<li>Informatica<\/li>\n\n\n\n<li>Ataccama<\/li>\n\n\n\n<li>IBM Infosphere<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>5. Test Automation Tools<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Selenium (UI components)<\/li>\n\n\n\n<li>JMeter (performance)<\/li>\n\n\n\n<li>QuerySurge (data testing)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>6. Cloud Big Data Tools<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Amazon EMR<\/li>\n\n\n\n<li>Google BigQuery<\/li>\n\n\n\n<li>Azure HDInsight<\/li>\n<\/ul>\n\n\n\n<p>A modern QA engineer must be comfortable with at least three to four of these tools.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Challenges in Big Data Testing<\/strong><\/h1>\n\n\n\n<p>Big Data Testing is complex because of:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. Massive Data Volume<\/strong><\/h3>\n\n\n\n<p>Traditional validation is impossible.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2. Multiple Data Formats<\/strong><\/h3>\n\n\n\n<p>Text, unstructured logs, media files, IoT data, etc.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>3. Distributed Systems<\/strong><\/h3>\n\n\n\n<p>Testing across clusters requires understanding distributed computing.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>4. Real-Time Data<\/strong><\/h3>\n\n\n\n<p>Streaming data poses unique testing challenges.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>5. Performance Bottlenecks<\/strong><\/h3>\n\n\n\n<p>Optimizing queries, workflows, and pipelines is not simple.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>6. Data Security<\/strong><\/h3>\n\n\n\n<p>PII and sensitive data require strict validation.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>How QA Testers Perform Big Data Testing (Step-by-Step)<\/strong><\/h1>\n\n\n\n<p>Here is a real-world workflow used in enterprise testing projects:<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 1: Validate Data from Source Systems<\/strong><\/h2>\n\n\n\n<p>QA ensures:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Correct data extraction<\/li>\n\n\n\n<li>Schema alignment<\/li>\n\n\n\n<li>No missing fields<\/li>\n\n\n\n<li>No corrupt files<\/li>\n<\/ul>\n\n\n\n<p>Tools: SQL, Python, Talend, Informatica<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 2: Validate Data Loading<\/strong><\/h2>\n\n\n\n<p>Check whether:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data loaded correctly into HDFS\/Hive<\/li>\n\n\n\n<li>File formats are accurate<\/li>\n\n\n\n<li>Data partitioning works<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 3: Validate Transformations<\/strong><\/h2>\n\n\n\n<p>Using Hive\/Spark SQL:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Aggregations<\/li>\n\n\n\n<li>Filters<\/li>\n\n\n\n<li>Joins<\/li>\n\n\n\n<li>Business logic rules<\/li>\n\n\n\n<li>Data cleansing<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 4: Execute Functional Testing<\/strong><\/h2>\n\n\n\n<p>Validate:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Workflow triggers<\/li>\n\n\n\n<li>Business rules<\/li>\n\n\n\n<li>Correct execution of Spark\/Hadoop jobs<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 5: Performance Testing<\/strong><\/h2>\n\n\n\n<p>Use tools like JMeter or custom scripts to evaluate:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Job latency<\/li>\n\n\n\n<li>Throughput<\/li>\n\n\n\n<li>Cluster behavior under load<\/li>\n\n\n\n<li>Node scalability<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 6: Data Quality Testing<\/strong><\/h2>\n\n\n\n<p>Use DQ tools to check:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Duplicates<\/li>\n\n\n\n<li>Missing values<\/li>\n\n\n\n<li>Formatting issues<\/li>\n\n\n\n<li>Data integrity<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 7: Security Testing<\/strong><\/h2>\n\n\n\n<p>Test for:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Encryption<\/li>\n\n\n\n<li>Authentication<\/li>\n\n\n\n<li>Authorization<\/li>\n\n\n\n<li>Data access logs<\/li>\n<\/ul>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Real-Time Examples of Big Data Testing<\/strong><\/h1>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Example 1: Banking Fraud Detection<\/strong><\/h3>\n\n\n\n<p>Testing real-time Kafka + Spark Streaming pipelines that detect fraud.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Example 2: Healthcare Data Validation<\/strong><\/h3>\n\n\n\n<p>Ensuring EHR (Electronic Health Record) data is accurate and compliant.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Example 3: Retail Customer Behavior Analytics<\/strong><\/h3>\n\n\n\n<p>Validating billions of clickstream logs used for recommendation engines.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Example 4: Telecom Usage Analytics<\/strong><\/h3>\n\n\n\n<p>Testing Hadoop\/Spark systems that handle millions of daily call logs.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Skills Needed to Become a Big Data QA Tester<\/strong><\/h1>\n\n\n\n<p>A QA professional must know:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>SQL (advanced)<\/li>\n\n\n\n<li>HiveQL \/ SparkSQL<\/li>\n\n\n\n<li>Hadoop\/Spark basics<\/li>\n\n\n\n<li>ETL testing<\/li>\n\n\n\n<li>Data validation techniques<\/li>\n\n\n\n<li>Automation basics<\/li>\n\n\n\n<li>Performance testing<\/li>\n\n\n\n<li>UNIX commands<\/li>\n\n\n\n<li>Cloud platforms<\/li>\n\n\n\n<li>Python (optional but powerful)<\/li>\n<\/ul>\n\n\n\n<p>Learning these skills is a core part of any strong <strong>Software testing and quality assurance course<\/strong> or <strong>Quality assurance tester training<\/strong> designed for today\u2019s job market.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Why Big Data Testing Is a Must-Learn Skill for QA Professionals<\/strong><\/h1>\n\n\n\n<p>Big Data is not slowing down. Companies are hiring QA testers who understand how to validate large-scale data systems.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Massive demand in every industry<\/li>\n\n\n\n<li> High-paying job roles<\/li>\n\n\n\n<li> Opportunity to work on data-heavy enterprise systems<\/li>\n\n\n\n<li> Essential for modern digital transformation projects<\/li>\n\n\n\n<li> Increases your value as a QA engineer in 2025 and beyond<\/li>\n<\/ul>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Conclusion<\/strong><\/h1>\n\n\n\n<p>Big Data Testing is now a core skill for modern QA professionals. With data becoming the heart of every business decision, ensuring its accuracy, integrity, performance, and security is more important than ever. Successful Big Data Testing requires a strong understanding of distributed systems, ETL pipelines, data validation, SQL, performance analysis, and data quality frameworks.<\/p>\n\n\n\n<p>If you are preparing for a career in quality assurance or want to advance your QA skills, enrolling in a <strong><a href=\"https:\/\/www.h2kinfosys.com\/courses\/qa-online-training-course-details\/\">Quality assurance tester training<\/a><\/strong> can help you build the expertise required to work on large-scale enterprise data systems. From Hadoop to Spark, and from ETL testing to performance optimization, Big Data Testing opens doors to some of the most exciting QA roles in the industry.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Big data is no longer a buzzword. From healthcare and finance to e-commerce and entertainment, massive volumes of data are now the backbone of decision-making. But with such enormous amounts of structured, semi-structured, and unstructured data flowing through distributed systems, ensuring data accuracy, quality, performance, and reliability has become a critical priority. This is where [&hellip;]<\/p>\n","protected":false},"author":20,"featured_media":9679,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[],"class_list":["post-9670","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-qa-tutorials"],"_links":{"self":[{"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/posts\/9670","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/comments?post=9670"}],"version-history":[{"count":1,"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/posts\/9670\/revisions"}],"predecessor-version":[{"id":31987,"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/posts\/9670\/revisions\/31987"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/media\/9679"}],"wp:attachment":[{"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/media?parent=9670"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/categories?post=9670"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.h2kinfosys.com\/blog\/wp-json\/wp\/v2\/tags?post=9670"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}