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Domo

Domo puts data to work for everyone so they can multiply their impact on the business. Our cloud-native data experience platform goes beyond traditional business intelligence and analytics, making data visible and actionable with ...Read more about Domo

4.3 (296 reviews)

5 recommendations

Zapier

Founded in 2011, Zapier has helped over 1.8 million individuals and businesses with their automation needs. Zapier moves info between your web apps automatically, so you can focus on your most important work. Build custom workfl...Read more about Zapier

UiPath

UiPath is an on-premise data entry and robotic process automation solution designed for businesses of all sizes. The solution allows users to create, deploy and administer automation in business processes. UiPath features UiP...Read more about UiPath

Process Street

Process Street is the world's first Process Management Platform powered by AI. We help teams share their core processes, then transform them into powerful no-code workflows. Start with employee onboarding to set up new hires for ...Read more about Process Street

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Anypoint Platform

Anypoint Platform is an application development solution for organizations that are looking to integrate applications, data sources and devices using application programming interfaces (API). The solution is suitable for industrie...Read more about Anypoint Platform

Make

Make is a visual platform that helps businesses of all sizes design, build, and automate anything, from tasks and workflows to apps and systems. Use the playful drag-and-drop interface to connect apps in a few clicks, and build l...Read more about Make

Albato

Albato is a no-code platform designed to streamline and automate workflows by integrating various applications. Users can create automation, select the origin application, and select the destination platform. It includes a no-co...Read more about Albato

Salesforce Platform

Salesforce Platform is an enterprise platform-as-a-service (PaaS) solution that allows developers to build, test and resolve defects in cloud applications before deployment. The platform provides tools and services to automate bus...Read more about Salesforce Platform

Boomi

Boomi is the world’s most popular, independent, cloud-native integration and automation platform. Boomi simplifies digital landscapes, so it’s easier to streamline customer experiences, automate business processes, and adopt new t...Read more about Boomi

IFTTT

IFTTT is a data integration software, which helps fintech, home automation, and energy companies connect applications and devices with third-party integrations. The software allows financial institutions to connect apps or website...Read more about IFTTT

Microsoft Power Automate

Power Automate by Microsoft is an advanced automation platform that provides a diverse range of capabilities such as BPA, DPA, RPA, process/task mining, and AI-powered automation. With Power Automate, users can efficiently manage ...Read more about Microsoft Power Automate

Power My Analytics

Power My Analytics is the only solution that enables businesses to automate marketing reports with one click. It enables users to connect to popular data sources, such as Google Analytics, Salesforce, and Microsoft Dynamics CRM, a...Read more about Power My Analytics

APPSeCONNECT

APPSeCONNECT is an intelligent integration platform (iPaaS) that connects applications and automates business processes. The platform has an in-built low-code visual integration designer "ProcessFlow" that helps users build anyt...Read more about APPSeCONNECT

TeamDynamix

TeamDynamix is a no-code, cloud-based IT Service Management (ITSM) and Project Portfolio Management (PPM) platform with enterprise integration & automation. Whether you are just starting out with ITIL or a best-in-class ITIL sho...Read more about TeamDynamix

Amaka

Amaka is a cloud-based solution, designed to help small to midsize businesses connect with accounting applications and automate the data entry process. Users can synchronize sales and transactional data with Xero, Quickbooks, MYOB...Read more about Amaka

CI HUB Connector

CI HUB is the ultimate digital supply chain connector, providing businesses using Adobe CC, Office365, Google Workspace a direct connection to DAM/MAM/PIM systems, including asset libraries. Instantly integrated, it is a key com...Read more about CI HUB Connector

Tuvis

Tuvis is a solution that provides the integration between WhatsApp & Salesforce or Microsoft Dynamics 365 for direct Agent-to-Customer chat interactions. It enables Sales, Customer Service, and Support teams to communicate with ...Read more about Tuvis

ePayPolicy

ePayPolicy is a payment processing solution designed to help businesses in the insurance sector collect credit card and ACH payments from policyholders. The centralized dashboard enables administrators to track transactions, acces...Read more about ePayPolicy

ImportOmatic

ImportOMatic is a data integration solution for Blackbaud's Raiser's Edge and Raiser's Edge NXT fundraising solutions. It is deployed as a plug-in for the Raiser’s Edge platform. ImportOMatic allows users to filter and transf...Read more about ImportOmatic

SyncSpider

SyncSpider is an application-to-application integration tool designed to help eCommerce businesses grow revenue using multichannel sales automation. It helps manage stock in a centralized place, connect with eCommerce tools to syn...Read more about SyncSpider

Buyers Guide

Last Updated: March 16, 2023

The data universe is expanding. It's no secret that the data businesses create, capture and analyze has been growing in volume and diversity, with no signs of slowing down.

The ubiquity of data in today's business environment dictates that even small businesses should be thinking of how they can use data for a competitive advantage. Increasingly, tools are becoming available to help with the collection and analysis of this data.

In this guide, we'll cover:

What Are Data Integration Tools?

Data integration is simply the process by which data is collected from multiple sources, normalized and prepared for analysis. Data integration software are tools that collect and transform the data for common storage, typically in a data warehouse, from which it can be extracted for analysis, as depicted in the diagram below:

Data-integration-and-analysis-process-(diagram)

Traditionally, this is done through the extract, transform, load (ETL) process by a database administrator (DBA), who sets up the criteria the data should adhere to prior to storage. The criteria the DBA sets up, or defines for the data, are based on the most critical insights a business seeks to derive from the data.

The ETL process is an involved one in which data is collected, or "extracted" from the original sources, which often exist in widely varying formats. These include not only .CSV and XML files, but also online sources such as social media.

Once the data is extracted from the original source, it is "transformed" into a format that fits the parameters the DBA has defined for the data warehouse, or wherever the data will reside.

Conversely, the ELT (extract, load, transform) process manages the process in a different order—one in which the data is loaded into the database, where it's transformed (as opposed to having predetermined rules set up within the database, such as a data cube).

Data-integration-environment-in-TIBCO-Jaspersoft-(screenshot)

Data integration environment in TIBCO Jaspersoft

Increasingly for large enterprises, data lakes are becoming a popular data storage strategy for those dealing with big data.

The data is then integrated with other transformed data for like comparisons and analysis.

Common Features of Data Integration Tools

As a baseline, data integration tools should offer the following:

ETL (extract, transform, load)

Collects data from outside sources, transforms it and then loads it into the target system (a database or warehouse). Because primary data is often organized using different schemas or formats, analysts can use ETL tools to normalize it for useful analysis.

ELT (extract, load, transform)

Collects data from outside sources, loads it into the database or warehouse and then transforms it to conform to requests for analysis. This feature allows the data to be manipulated/integrated within the warehouse itself, rather than prior to migration.

Data capture/connection

Allows software to "connect" to multiple—and sometimes disparate—data sources (including relational databases, XML, .CSV, data lakes, Hadoop, SQL etc.) for the purposes of data extraction.

Data transformation

Normalizes data across disparate sources by standardizing data, converting values and correcting numeric values to conform to minimum and maximum values.

Data quality management

Helps organizations maintain clean, standardized and error-free data. Standardization is especially important for BI implementations that integrate data from diverse sources, as this ensures that later analyses are correct.

Some data integration software offers additional features, including more self service options (such as drag-and-drop development for citizen data analysts).

What Type of Buyer Are You?

Typically, data integration resides in the realm of the DBA, who sits in the IT department.

Small businesses. These are businesses with little to no IT department. While traditionally, they have less need to manage vast amounts of data in a data warehouse, this trend is shifting, given the explosion of data in recent years. More and more tools designed to help "citizen" data administrators extract, integrate and manage data without the need for extensive programming knowledge are becoming available today.

Midsize businesses. These buyers are still likely to benefit from data integration tools that offer some level of self-service functionality, so that a robust IT department isn't required to architect complex data storage solutions. Real-time data demands and ad hoc granular data analysis are becoming the norm.

Enterprise businesses. These buyers will have a robust IT department capable of handling the traditional ETL process, which involves time and effort. Ironically, these larger enterprises may have more of a demand for real-time delivery of multistructured data as opposed to the “batch" delivery methods ETL is associated with. Increasingly, tools are becoming more and more sophisticated, with broader functionality sets from delivery to governance, to meet these demands.

Benefits of Data Integration Tools

Data Integration software provides two clear benefits to users:

  • Single source of truth. The principal benefit of data integration software is arriving at a single source of truth for businesses, especially those that deal in a variety of data sets from multiple, and often incongruous, sources. The "truth," or insight sought after, is typically a key performance indicator (KPI) defined by the business. Data integration aligns the data to best reveal this truth.

  • Apples to apples. The additional benefit is that organizations both large and small can not only define what they need from the data to make the most important business decisions, but confidence in those insights. Integration of data into a consistent, predetermined view ensures to some degree that like-comparisons are being made. In short, integration allows for the best "apples-to-apples" comparison disparate data sources can provide.

Market Trends to Understand

Data integration as a field is undergoing some change. According to Gartner, data integration and quality tools as a market grew 2.5 percent in 2016 to $4.4 billion, though more traditional data integration tools, which serve merely as "connectors" for batch movement of data, had slower growth (report available to Gartner clients).

This is due in large part to the increasing "mass proliferation" of data according to Gartner, which has put greater demand on data integration tools to expand their offerings to serve various data delivery speeds, deployments and types.

Essentially, slow, plodding, structured data delivery is on the outs. More and more, enterprises are seeing the need for data integration flexibility, including virtual and real-time data delivery, as well as the ability to deal with hybrid data sources (cloud and on-premise). Also, businesses are looking more and more for data integration tools that can handle "multistructured" data, or data that comes in a diverse array of structures.