Five things you should know about creating a modern data stack with

  1. is a platform with deep capabilities that extracts data from disparate sources, loads that data to a warehouse or lake, and then transforms data into the correct format for analytics.
  2. As a result, you run datasets through BI tools like Looker and Tableau and generate business-critical insights.
  3. lets you move data between locations without any coding or data engineering experience.
  4. A data integration tool like is just one component of your modern data stack. You will also need to invest in a cloud data warehouse or lake and choose a BI platform.
  5. More control over your data and improved data compliance are some of the benefits of a modern data stack. is a company that provides an ELT (Extract, Load, and Transform) data stack. The platform executes data transformations using DBT, which stands for Database Transformation toolkit and pushes push the data into systems like Salesforce. gives you more control over your data and provides a cost-effective solution to data integration.

Table of Contents is a new ETL platform that will become one of the most critical components of your modern data stack. With its deep e-commerce capabilities, no-code connectors, and jargon-free environment, you can move data to your chosen location without breaking a sweat. Schedule a 7-day demo today. 

What Is a Modern Data Stack?

A "data stack" is the set of technologies used to build an end-to-end solution for enterprise-wide integration. The goal here is to control your data and lower costs. The modern data stack is hosted in the cloud, making it quick and easy for end-users to access the data. It also helps with scaling by removing costly downtime from server instances that need more memory or storage capacity than what they already have available.

A modern data stack uses cloud-based technologies to facilitate data integration. That brings all kinds of benefits to businesses that want to scale their data integration projects, safeguard data in a virtual environment, and access data from any location in the world. Legacy data stacks, on the other hand, rely on physical infrastructure such as local servers, which can be expensive to maintain and increase the risk of data loss. If a local server gets damaged in a flood or fire, for example, an organization may never recover its business-critical data.

Benefits of a Modern Data Stack

There are multiple benefits to using a modern data stack, including:

  • More control over your data.
  • Decreased costs for end-users and increased profits for businesses that use the stack to provide services. Better compliance with regulations by having a central location where all the information is stored. That helps you comply with data governance regulations such as GDPR, HIPAA, and CCPA. By adhering to these frameworks, you can avoid expensive penalties for violating data protection legislation and maintain the trust of clients who want to protect their sensitive business-critical data. 
  • Removes costly downtime by having everything in the cloud and scaling when needed.
  • There's no limit on how much bandwidth or size your company can handle between all of these systems.
  • Keeping data in the cloud can reduce the risk of data loss if physical hardware gets damaged or stolen. 

What Is an ELT, And Why Is It Essential to a Modern Data Stack?

Extract, Load, and Transfer (ELT) describe a sequence of moving data to a warehouse or lake and preparing it for data analytics.. first extracts data from one system and then loads it into a data warehouse like Snowflake. Next, the platform utilizes the ample storage of the data warehouse or lake to run queries that provide your business with real-time intelligence.

When you pull data out of your SQL server, Google Ads, Salesforce, or any other system whose data is helpful to your business, you essentially want to extract it out of the silo and into the warehouse. Many tools like specialize in the extract and the load of an ELT process by allowing you to focus most of your energy on the T, the transformation. 

You can monitor for changes in the source system and keep your data warehouse in sync in near real-time. With a few buttons, these tools can extract from hundreds of data sources and load data into the most popular data platforms, including the big data warehouses like Snowflake, Redshift, and BigQuery, and regular OLTP databases like Postgres, Oracle, MySQL, or SQL Server.

Besides performing the extract and load, also allows you to do transformations before and after the data loading. You might think that once the raw data is in your data warehouse you're done. The problem, however, is that raw data is usually really messy, and you can end up with redundancies, duplicate records, and missing information even if your data is super clean.

Because of this, you might join up all this data together across silos to get broader pictures of your business. Fixing these problems is the job of the transformation step. However, your business can build a robust and efficient transformation pipeline with an open-source tool called DBT.

Components of the Modern Data Stack

Your modern data stack (or MDS) will include various data integration tools, such as: 

ELT Data Pipeline

A managed ELT data pipeline extracts data from its source and loads that data to another location. 

Recommended reading: What is ELT?

Data Warehouse/Data Lake

A cloud data warehouse or data lake serves as the central location for all the data that flows in and out of your business.

BI Tools

Once you have loaded data into a data warehouse or lake, you can transform data into the appropriate format for analytics and run it through cloud-based business intelligence (BI) analytics tools. That lets you generate real-time intelligence about your business. 

Data Integration Tool

Building data pipelines requires lots of code and programming, and the process can be cumbersome if you lack data engineering experience. That's why most data-driven companies use a cloud-based data integration tool to move data from sources to a warehouse or lake and then to third-party BI data tools. 

Say you own an e-commerce company. You can create a data pipeline that moves e-commerce data from several sources (a relational database, transactional database, customer relationship management system, etc.) to a centralized location and then transform that e-commerce data for big data analytics. You can then use third-party BI tools to produce data visualizations, data models, and machine learning models about products and customers so you can improve day-to-day marketing, sales, and customer service tasks.

The modern data stack is the foundation of any data integration project because it contains all the technologies an organization requires to move data between locations and generate analytics. It helps identify trends and patterns in disparate data sources so companies like yours can make better decisions and solve problems. 

Choosing the Right Components for Your Modern Data Stack

Here are some things to consider when choosing the components for your modern data stack.

Data Warehouse/Data Lake

Think about factors such as price, scalability, implementation time, and maintenance when choosing a cloud-based warehouse or lake. 

Recommended reading: What is a Data Warehouse and Why Are They Important?

BI Tool

Pick a BI tool that offers data analysis functionality for your niche. If you own an e-commerce company, for example, use a tool that generates high-quality data visuals for products, customers, and sales performance. Also, consider a tool that lets you customize dashboards and reports based on your specific data requirements.

Recommended reading: Top 17 Business Intelligence Tools Of 2022

Data Integration Tool

Choose a data integration tool like with pre-built data connectors that allow you to extract, load, and transfer data such as e-commerce information without any code. has connectors for relational databases, transactional databases, SaaS tools, CRM systems, enterprise resource planning (ERP) systems, and more. 

Other Ways to Build a Modern Data Stack

You can build a modern data stack with other data integration methods apart from ELT. Consider these ELT alternatives when moving data from one location to another:

Extract, Transform, Load (ETL)

ETL swaps the 'load' and 'transform' functions of ELT. It extracts data from a source such as an e-commerce system, transforms it into the correct format, and loads that data to a warehouse or lake. 


If you want to move data from a warehouse or lake to an operational system such as a SaaS tool, consider ReverseETL. 


Change Data Capture (CDC) syncs data from two or more data sources and monitors changes made to data in those systems. That provides you with access to the latest data in your organization in real-time and minimizes disruptions to workflows. lets you move data from disparate sources to a warehouse or lake via ELT, ETL, ReverseETL, super-fast CDC, and other data integration methods without any of the hard work. The platform's philosophy is to solve the challenges of building a modern data stack by providing a jargon-free environment for data integration. Schedule a 7-day demo now. 

Why Use for Your ELT Pipeline is an all-in-one data integration platform. It provides an end-to-end data stack solution, which can help save time and money while also controlling your integration processes. helps with your ELT process and offers a no-code to low-code, easy-to-use graphical interface.

The ELT setup is made much easier through the backend. You can set up connections with various data sources, including popular ones like Facebook and Salesforce. You'll also be able to connect with obscure data sources to fit all of your business needs, no matter which industry you're in. The platform achieves this by providing a REST API component that allows you to connect to different sources that other tools may not connect to.

This transactional component is very flexible, allowing you freedom in setting up transformations at the field level or table level, depending on what suits you best.

For security, provides options for encryption/decryption and offers hashing functions along with masking of data to provide peace of mind. This gives freedom to you and your company and secures your business's sensitive PII. You can schedule and automate tasks with's scheduler when finishing a completed pipeline.

Companies that see themselves as growth-oriented would benefit significantly from utilizing what has to offer. was built for integration projects using ELT, master data management jobs, big data warehousing jobs, and more. The platform also lowers the barrier of entry for companies that are not data experts due to its easy-to-use interface and great support team.


The modern data stack can seem overwhelming at first, with so many options and tools available. is an excellent option for those businesses who want to integrate all of their sources into one location and have an easy-to-use interface that even beginners could understand.

Data integration is now easier than ever before with’s no code/low code graphical interface, which allows non-developers to build integrations without wasting valuable resources.

If your business wants to upgrade to a modern data stack, schedule a seven-day demo of's tools.