Organizations of all sizes and industries are looking for ways to enact digital transformations within their business, using new technologies to outperform their rivals and better serve their customers.
For these forward-thinking companies, big data has become an essential concern: the average company now manages 163 terabytes (163,000 gigabytes) of data. However, all this information is of little use without a strategy for effectively managing and integrating it to get valuable data-driven insights.
According to a study by the consulting firm McKinsey & Company, data-driven organizations are 23 times more likely to acquire new customers and 19 times more likely to be profitable than their competitors. It’s no wonder that 99 percent of executives say that they are working to build a data-driven culture in their organization.
Still, too many companies don’t know how to take advantage of all this information, or simply don’t have the technical chops. Data integration is a greater challenge than ever before: more data sources, new data types, and hybrid cloud and on-premises environments all present serious challenges. A survey by the software company Progress finds that data integration is the number one challenge for digital transformation.
The good news is that businesses that need data integration tools have a wide variety of alternatives at their fingertips. But how can you sort through all these data integration software options to find the right one for your needs and objectives? In this article, we’ll discuss some of the most popular data integration tools, and how you can select the best data integration tool for your situation.
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Table of Contents:
What is Data Integration?
As the term suggests, “data integration” refers to the act of collecting and combining information from multiple sources for the purposes of analysis and reporting. These sources may include sales and marketing data, customer support statistics, financial projections, and more.
The value of a single data point is next to nothing—information becomes exponentially more useful the more you have of it. Data integration allows you to see the big picture and find hidden insights that would otherwise go undiscovered.
Information may exist in many different formats and structures within your business. During the data integration process, this information needs to be standardized and unified. The final step is to migrate this data from disparate sources into a data warehouse or data lake, where it can be more easily accessed and analyzed.
One of the most important use cases for data integration is for companies to better understand their customers. Information from across the business—including finance, sales, marketing, research and development, production, and support—can help you better understand what your customers want and how you can provide it at maximum efficiency.
The Top 17 Data Integration Tools
1. IBM InfoSphere
InfoSphere is a data integration tool for extracting and transforming different data types. Its scalable runtime environment powers on-demand data integration across various sources and targets. The platform utilizes native API connectivity and parallelism. This way, it enables connection to DBMS, ERP software, and big data sources. Its streamlined interface allows non-technical users to provision data on demand. InfoSphere supports several data delivery options. These include bulk ETL, data replication, and data federation. Supported data quality functions include data profiling, standardization, enrichment, and matching.
Xplenty is another powerful, cloud-based data integration software. The tool has connectors for diverse data sources and SaaS applications. It also provides an intuitive graphical interface. The UI makes light work of building data pipelines and running ETL/ELT processes.
The cloud-based platform is elastic and scalable, and it automates vital workflows. With automated monitoring, security, and scheduling, analysts can focus on the data. Moreover, Xplenty provides many resources to streamline app development. For example, developers can use API services to enhance customization. Likewise, there are connectors to ease integration with apps, such as monitoring systems.
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3. Microsoft SQL Server Integration Services (SSIS)
Microsoft's SSIS is an SQL Server-based resource for managing data integration and transformations. You may use it to extract and transform data from different sources, such as relational databases and XML files. You can then load the data into a single or several data stores. It provides a simple graphical data integration interface. Thus, non-technical users can use it to develop solutions without writing programming codes. Also, SSIS has a rich set of built-in workflows. These automate and streamline data transformation and integration.
4. Informatica PowerCenter
Informatica provides a range of powerful data integration tools. It's suitable for multi-cloud, hybrid, or on-premise deployment. The resource supports many superfast connectivity options too. It has connectors for databases and data warehouses, enterprise applications, and Hadoop. It can also integrate with messaging apps and midrange systems.
With Informatica, you can ingest different data formats for transformation. Examples include XML, COBOL copybooks, and SWIFT. The tool also facilitates automatic intercompany exchange. This secure connectivity lets business partners share and collaborate on mission-critical data. Businesses can leverage Informatica's AI-driven data discovery to maximize data value, enterprise-wide.
Panoply is a self-service data warehouse in the cloud that claims to drastically simplify the task of collecting and analyzing your information. Data integration is included as one of the features of Panoply, but the solution also supports other capabilities such as schema modeling, storage optimization, and query performance optimization.
On the software review website G2Crowd, Panoply has an average rating of 4.5 out of 5 stars. Users praise the platform’s ease of use and customer support. However, they also mention that troubleshooting issues can be difficult, and the platform may not be a good fit for more complex ETL job flows.
As a cloud service, Panoply is only a suitable solution for companies who have already migrated their data away from on-premises databases. If you’re already fully committed to the cloud, however, Panoply is worth the look.
6. Oracle Data Integration Platform (DIP)
Oracle DIP is a cloud-based data integration solution that supports data governance processes. With the open platform, you can integrate data from within Oracle and hundreds of non-Oracle sources. It uses machine learning-driven automation to meet your data integration requirements faster. The tool is ideal for real-time data replication, profiling, enriching, and transformation. Oracle DIP has an intuitive visual interface. The UI simplifies data integration tasks, enabling business users to extract value much faster.
Talend offers a graphical interface for setting up and administering integrations without coding. The tool supports many connectivity options for cloud and on-premise data sources. It has connectors for social media and apps such as Salesforce, Box, and Marketo. Thus, you may leverage its cloud API services for both app and data integration.
Talend provides a collaborative cloud-based application for data quality control. It enables teams to collaborate on data curation tasks. The software has big data integration capabilities too. These allow you to ingest and manage large datasets with Spark and machine learning.
8. SAP Data Services
With SAP Data Services, you can integrate structured and unstructured data sources. The tool enables integrations with SAP and non-SAP data stores. It also supports enterprise applications connectivity (in the cloud or on-premise). It's compatible with data warehousing platforms such as IBM Db2 and Microsoft Azure.
You may use the resource to extract and analyze unstructured documents. For this purpose, SAP supports 220 different file and text formats. The integrator can also process semi-structured data across 31 languages for analytics. It powers data curation with prebuilt address and data cleaning modules. Also, it employs parallel processing and grid computing. These capabilities help to drive high-volume data profiling and transformations.
You can stream all your enterprise data into one cloud-based location with HVR. The solution supports intra-cloud, inter-cloud, and cloud-on-premise integration. It's also possible to load your data into several targets from a single source. Integrations are possible with data sources like AWS, Azure, Db2, and Salesforce.
By using log-based change data capture (CDC), HVR enhances real-time data replication. And the use of proprietary compression optimizes storage space. Additionally, the tool is versatile and scalable. That's because it incorporates a distributed architecture and various topologies.
Hitachi Pentaho powers the efficient integration of data from diverse heterogeneous sources. Thanks to metadata injection, the platform speeds up the onboarding of complex datasets. It also provides many prebuilt, reusable templates. These help to streamline and speed up data retrieval, preparation, and blending. Pentaho's multithreaded engine scales to match growing data integration needs.
The platform offers the option to use in-cluster execution along with data-processing engines. Combining these resources increases capacity for collaboration, maximizing data productivity. Pentaho also supports big data integrations. Compatible sources include Spark, NoSQL data warehouses, and Hadoop distributions.
11. InterSystems Ensemble
Ensemble is a cloud-based solution that facilitates data and application integration. It has an extensive adapter library to deliver out-of-the-box connectivity. Thus, it enables you to access and process different file formats from standard and non-standard data sources. Supported technologies/protocols include Email, FTP, SAP, SQL, and HTTP.
What if you needed to build a custom adapter on the platform? Object inheritance and SOAP services would enable you to do that. Ensemble supports healthcare, business, and government data integration applications.
12. Information Builders
Information Builders provides a suite of data integration services. These are ideal for both conventional and non-conventional data sources. It also serves big data consolidation purposes. So you can use it to retrieve data from mobile apps, social media, and IoT devices. One of its outstanding features is B2B integration. The service enables business partners to share and track transactional data.
The cloud-based solution supports automated ETL processes. These simplify the creation and expansion of data warehouses or even data marts. Information Builders offers a broad array of off-the-shelf adapters too. The tools enable users to access and extract value from different data formats.
13. SAS Integration Studio
SAS Data Integration Studio has the features required to streamline data consolidation. One of its key features is a shared metadata environment. This architecture enhances the consistency of data standardization across all data sources. The software delivers connectivity for different data formats and platforms too. These include messaging apps, ERP, RDBMS, XML, and flat files. Other business-critical capabilities are ETL and data cleansing, enrichment, migration, and synchronization.
SAS Data Integration Studio supports data federation. The feature enables you to access and process data without moving it. Its intuitive graphical interface with repeatable workflows facilitates collaboration on data integration management.
14. Dell Boomi
Boomi is a scalable data integration solution. It can integrate on-premise and cloud apps, data stores, and IoT devices to provide a unified view of data. It has a host of connectors for diverse data sources. Supported platforms include Google Cloud, Amazon S3, NetSuite, and Microsoft Azure SQL Server.
The software helps with data mapping tools and various integration patterns. And a drag-and-drop UI simplifies workflows, even for non-technical users. Besides, Boomi includes prebuilt templates and process libraries. These features speed up the delivery of data integration projects.
Syncsort offers a comprehensive data integration suite for enterprises of all sizes. It comes with a set of big data connectors. These let you integrate various platforms to power advanced AI analytics. The software supports change data capture, database replication, and ETL processes. Thus, it has the right tools for data governance and data quality control.
With Syncsort, you can ingest IBM mainframe's operational machine data into Splunk. This integration gives you a full view of your IT environment.
16. Actian DataConnect
DataConnect provides hundreds of connectors for integrating on-premise and cloud data sources. The data integration tool lets you create reusable templates with the IDE framework. This way, you can scale by executing similar integrations superfast.
DataConnect features an intuitive graphical interface. With the UI, you need no scripting skills to develop job schedules or integration maps. Also, DataConnect incorporates REST Invoker 3.0. The easy-to-use resource simplifies the creation of web services with RESTful APIs.
17. Software AG WebMethods OneData
WebMethods OneData enhances data integration by delivering quality data from various sources. It lets you curate and validate your data. Doing this eliminates errors and redundancies across data sources, software systems, and processes. The platform supports multi-domain data modeling. Thus, it powers enterprise-driven integrations between customers, products, geospatial information, and reference data.
WebMethods OneData includes a metadata registry. So, it enhances standardization and the reusability of data components across business units. Additionally, it provides hierarchy management tools. Examples are versioning tools and a configurable business rules engine.
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How to Choose the Right Data Integration Tool
There are more data integration tools than any one company could possibly need or use, so you’ll have to choose your data integration software judiciously.
Adopting a “one-size-fits-all” approach is the wrong way to go about it when choosing a data integration tool. The issues to take into account here include:
- Your company’s situation: Different tools for data integration are better suited for companies of different sizes or industries, depending on the amount and the type of data you hold. Remember that as your business grows, so too will the volume and the complexity of the data you store.
- IT infrastructure: The constraints of your IT environment could mean that you prefer a cloud-based or an open-source data integration solution. Whether your data is stored on-premises or in a hybrid cloud setup, make sure that your data integration tool of choice is capable of working with it.
- The types of data sources and applications: According to an estimate by Forrester Research, companies use an average of 66 different SaaS (software as a service) applications. However, not all data integration tools are capable of working with all data formats and applications.
- Regulatory and compliance issues: Companies in certain industries such as finance, healthcare, and retail need to comply with regulations such as Sarbanes-Oxley, HIPAA, and PCI-DSS that govern how they store and treat sensitive private data. If this concern applies to you, make sure that you select a data integration tool that is compliant with all necessary laws and standards.
Read more about data integration best practices here.
Data integration is essential to developing a unified, trusted data warehouse. Are you looking for a cloud-based tool to integrate, clean, and transform all your data? Try out Xplenty today!