The five main reasons to implement a fully automated data pipeline are:

  1. To maximize returns on your data through advanced analytics and better customer insights.
  2. To identify and monetize "dark data" with improved data utilization.
  3. To improve organizational decision-making on your way to establishing a data-driven company culture.
  4. To provide easy access to data with improved mobility.
  5. To give easier access to cloud-based infrastructure and data pipelines.

When you think about the core technologies that give companies a competitive edge, a fully automated data pipeline may not be the first thing that leaps to mind. But to unlock the full power of your data universe and turn it into business intelligence and real-time insights, you need to gain full control and visibility over your data at all its sources and destinations. 

Table of Contents is a data integration solution for enterprises that want to build a fully automated data pipeline. With its deep e-commerce capabilities and an incredible range of data integration methods (ETL, ELT, ReverseETL, super-fast CDC, and more), you can move data from one location to another without additional hardware or hiring data engineers. Schedule a 7-day demo now. 

Advanced BI and Analytics

Almost all organizations struggle to extract the full value they need from their data and gain critical insights that drive organizational efficiency and improved performance and profitability. A fully automated data pipeline architecture allows your organization to extract data at the source, transform it into a usable form, and integrate it with other sources before shipping it to a data warehouse or data lake for loading into business applications and machine learning analytics platforms. By automating these processes, you can establish better data management practices, improve business intelligence, enhance data processing, facilitate workflows, and capture quality real-time insights.  

Recommended reading: Business intelligence vs. Data Analytics

Increased Data Utilization

As digitization speeds up, the amount of data companies collect increases, but most companies are still not close to fully utilizing their raw data and gaining deeper insights and real-time visibility from advanced analytics. In older systems and architectures, costly engineering talent must be deployed to move data and prepare it for integration and analysis. 

Turn Dark Data into Revenue-Generating Intelligence 

Gartner defines dark data as: 

"The information assets organizations collect, process and store during regular business activities, but fail to use for other purposes, for example, analytics, business relationships, and direct monetizing." 

Turning dark data into business intelligence and customer insights can yield significant outcomes for companies, which can use the information to strategize, improve internal processes, and generate revenue. Advanced analytics can point to opportunities to act quickly on emerging trends, or enlarge and scale profitable products and services. But how do organizations manage the data that is streaming in from every direction? Analyzing data in real-time from many different sources requires a fully automated pipeline that can easily process and orchestrate multiple events. 

For example, when one client needed better tools to reach their target markets and improve customer satisfaction, they knew they needed to improve their data mining and business analytics strategy. By adopting’s data integration solution, they were able to:

  • Get alerts by automatically pulling information from S3 buckets and Redshift and loading it into Salesforce
  • Standardize and transform their data formats so they could use the best features from Salesforce and Totango
  • Improve their predictive accuracy by pulling data from Salesforce, transforming the information into more useful segments, and putting the processed data back into Salesforce.

Learn more about three real-life applications where companies were able to improve their BI and data mining capabilities by implementing’s data integration platform and pipeline toolkit.

Fully Automated Data Pipeline: Faster Data Mobility

A fully automated data pipeline allows your business to function efficiently, moving data quickly across applications and systems, providing strategic real-time data and performance insights to leadership. On the ground, your data pipeline is a critical component in the infrastructure that delivers key performance indicators and other metrics to teams in marketing, sales, production, operations, and administration. 

Improved Organizational Decision-Making

The quality of your decision-making is directly tied to the availability of quality data. Getting accurate, timely data in front of decision-makers and leaders is paramount. No-code tools and powerful automation allow non-technical teams to build pipelines and data flows that capture meaningful intelligence from more business activities and customer interactions. Business users can pull data from multiple sources, reformat it in a graphical interface, and load it into analytics software for real-time reporting, data analysis, and visualizations. 

Better Customer Insights

A fully automated data pipeline facilitates the flow of data between systems, eliminating the need to manually code and format data, and allowing transformations to happen on-platform, empowering real-time analytics and delivering granular insights. Integrating data from different sources produces better business intelligence and customer insights.

Recommended reading: What is Customer Data Ingestion?

Establish a Data-Driven Culture

From targeted marketing to more efficient operations and improved performance and productivity, data is a key driver. Collecting data allows businesses to measure and quantify their assumptions and outcomes, but to drive a data-based culture across the organization, these practices can not remain in the executive suite. They have to trickle down to each team and employee. By empowering employees with the tools they need to capture value from data, companies create a data-driven culture from the ground up.

Easy Access to Cloud-Based Data Architecture and Data Pipelines 

By 2022, it is estimated that the cloud will be essential for 90% of advanced analytic functions and innovation. As new technologies converge and emerge on the edge, the data pipeline will become even more essential. Regardless of how tools and platforms evolve, being able to quickly move and transform data will remain fundamental. Cloud-native technologies are elastic and scalable, and allow businesses to be flexible as they grow and to adapt quickly to changing conditions.  These businesses no longer have to rely on on-premises systems when managing e-commerce data, for example. 

No matter what technologies you add to your stack, your data pipeline is the heart of your data infrastructure, pumping data across systems and applications, and delivering superior business intelligence and analytics across the entire organization.

How Helps You Implement a Fully Automated Data Pipeline is a new data integration platform with deep e-commerce capabilities that helps you build a fully automated data pipeline from scratch without the complicated bits.’s philosophy is to solve the challenges of data integration by providing a jargon-free environment that anyone can use, even if they lack data engineering experience. 

The platform offers various data integration methods for building a fully automated data pipeline. These include: 

Extract, Transform, Load (ETL): extracts data from sources such as e-commerce systems, transforms data into the proper form for analytics, and loads it to a data warehouse. From here, you can run data through BI tools and generate intelligence about your organization for improved decision-making and problem-solving.

Extract, Load, Transform (ELT): extracts data from sources, loads it to a warehouse, and then transforms the data for analytics. ELT suits larger data loads that ETL typically can’t handle: for example, thousands of data sets from an e-commerce system. 

ReverseETL: extracts data from a warehouse, transforms it into the correct format, and loads it to an operational system for SaaS, helping companies like yours benefit from a fully automated data pipeline. 

Change Data Capture (CDC): syncs two or more data sources and monitors changes made to these systems so you have the latest information at all times. 

Whatever method you choose, helps you build a fully automated data pipeline with its:

  • Out-of-the-box no-code connectors that require no programming or data engineering experience.
  • Online tutorials and guides. 
  • Exceptional customer service.
  • Unique pricing model that charges you for the number of connectors you use, not the amount of data you require. 
  • Ability to cleanse data so it complies with data governance regulations like GDPR. 

Now you can scale your data pipelines seamlessly without investing in additional hardware or engineering staff. You also don't have to worry about complicated concepts like schemas, data streaming, data aggregation, or programming languages like Java. 

Want to learn more about how is helping businesses improve their business intelligence and analytics with its cloud-based ETL solution? Get in touch to schedule a 7-day demo.