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A Complete Guide to ETL test automation

In these busy times that we live in, technologies are expanding, evolving, and transforming every day. We are today introduced to new technical terms frequently, giving us a sense that digital space has taken an invincible part in our lives. Whenever we talk about technology, we may change the operating methods or overall interaction process, but one thing remains constant – the data. In other words, whatever we do with technology, we are constantly generating data. Table Of Contents


Why ETL is Critical for Ecommerce Data Success & How to Start

It’d be hard to find anyone who’d say that taking a data-driven approach to business decisions is not worthwhile. Yet, so many businesses aren’t doing it because, as simple as it may sound on paper, it takes a great deal of strategic planning to pull off. One of the most crucial tools when it comes to accomplishing a data-driven decision-making process is known as ETL.


Introducing Datastream for BigQuery

In today’s competitive environment, organizations need to quickly and easily make decisions based on real-time data. That’s why we’re announcing Datastream for BigQuery, now available in preview, featuring seamless replication from operational database sources such as AlloyDB for PostgreSQL, PostgreSQL, MySQL, and Oracle, directly into BigQuery, Google Cloud’s serverless data warehouse.


How a Tour Operation Company Used Data to Improve Their Customer Experience

The customer journey is the decision-making process each buyer goes through before converting to a paying customer of your business. Mastering this journey will require an in-depth understanding of each stage and how you can continually improve your efforts. To understand this journey, you need to take a customer-centric approach, putting yourself in your customer’s shoes to understand their point of view.


Top 7 ETL Tools for 2022

Organizations of all sizes and industries now have access to ever-increasing amounts of data, far too vast for any human to comprehend. All this information is practically useless without a way to efficiently process and analyze it, revealing the valuable data-driven insights hidden within the noise. The ETL (extract, transform, load) process is the most popular method of collecting data from multiple sources and loading it into a centralized data warehouse.


What is the Best ETL Method for Data Analysis?

The five critical elements of ETL methods for analyzing data: ETL is a critical process necessary to discover the nuggets of truth locked inside a business’s vast ocean of data. Different data points, once analyzed as a whole, help businesses make smarter, more informed decisions. Companies that create substantial data figures, all coming from different, separate sources, find that ETL impacts the business’s decisions considerably. But what is ETL?


Zero-ETL approach to analytics on Bigtable data using BigQuery

Modern businesses are increasingly relying on real-time insights to stay ahead of their competition. Whether it's to expedite human decision-making or fully automate decisions, such insights require the ability to run hybrid transactional analytical workloads that often involve multiple data sources. BigQuery is Google Cloud’s serverless, multi-cloud data warehouse that simplifies analytics by bringing together data from multiple sources.


What Is ETL, and Why Should Ecommerce Businesses Use It?

Here are five things to know about ETL and how it benefits your Ecommerce business: Think about all the data that exists in your Ecommerce business. That might include customer data, inventory data, sales data, advertising data, and social media data. Now think about all the software and systems that store that data. These might include transactional databases, relational databases, customer relationship management (CRM) systems, enterprise resource planning (ERP) systems, and SaaS tools.


Challenges of Textual Data and the Progression of Textual Analytics

In the beginning, simple systems collected data, wrote data to files, and created reports. For the most part, these systems operated on transaction-based data—bank deposits, sales, telephone calls, and the like. An entire infrastructure supported these essential business systems, but there was little or no place for text. All data was highly and tightly structured, and text was ignored.


How Do I Enrich My Data: Data Management and ETL

Five things you need to know about how to enrich data ETL: All business decisions happen based on the data that’s available. It makes sense, then, that the more detailed that data is, the more effective those business decisions can be. That’s where data enrichment comes in. When e-commerce companies enrich data, they can improve data analysis and business intelligence and make smarter, more informed decisions.