As a hybrid data approach, the IBM Db2 suite of products integrates all aspects of data management and analytics – for both relational and object-oriented data models – within a single, highly-compatible family of tools and technologies. IBM Db2 offers RDBMS, data warehousing, and data engine tools for cloud-based systems and on-premises systems. Plus, with Integrate.io’s native Db2 connector, you can instantly connect to any piece of the IBM Db2 toolkit to leverage Db2's capacity to share, access, and analyze both structured and unstructured data – no matter where it is located.
Intercom is a powerful set of tools for better managing your company’s customer support system. It includes a help center with a feedback system, which you can use to focus future articles on the growing needs of your customers, and it also provides a robust conversation system that allows you to assign support teams to customers based on specific criteria (about the customer or discussion topic), rather than just based on availability. Intercom is designed to create a more effective customer support network by specifically tracking and targeting your customers’ needs.
Bring all your Intercom data to Amazon Redshift
Load your Intercom data to Google BigQuery
ETL all your Intercom data to Snowflake
Move your Intercom data to MySQL
Db2 Database is a relational database management system (RDBMS) optimized for high-performance transactional workloads. As an operational database management system, Db2 Database is not only highly performant and reliable, but it also allows you to derive actionable insights from your operational data. Db2 Database delivers advanced features like in-memory technology, storage optimization, continuous data availability, workload management, and cutting-edge management and development tools. Db2 Database is compatible with Windows, Linux, and Unix.
Db2 on Cloud is a fully-managed, SQL-based transactional database that runs on the cloud. One of the defining characteristics of Db2 on Cloud is its high-availability option, which delivers 99.99% uptime (according to IBM). This cloud-based database offers automatic security updates and independently scalable storage and processing, which automatically scales resources up and down based on usage requirements. Available on AWS and IBM Cloud, Db2 on Cloud delivers advanced features for backup and recovery, encryption, and data federation. Through its private networking features, you can also deploy Db2 on Cloud on a private network accessible over a secure VPN. Db2 Hosted is the hosted, unmanaged version of the Db2 on Cloud SQL-based cloud database.
As a data management system optimized for high-speed read operations, data aggregation, and analysis, IBM Db2 Warehouse has evolved over time to offer a range of advanced analytics and data management features. Db2 Warehouse allows you to combine data from various transactional and operational database systems, and analyze it to find deep insights, patterns, and hidden relationships. Db2 Warehouse supports a range of data types, machine learning algorithms, analytical models. For example, Db2 Warehouse supports relational data, non-relational data, geospatial data, multi-parallel processing, predictive modeling algorithms, in-memory analytical processing, Apache Spark, RStudio, XML data, embedded Spark Analytics engine, and more. Db2 Warehouse runs on-premises, on the private cloud, and on various public clouds as a managed or unmanaged solution.
Db2 Warehouse on Cloud (formerly known as “dashDB for Analytics”) is a fully-managed, highly-scalable, cloud-based data warehouse management system. IBM optimized Db2 Warehouse on Cloud to perform compute-heavy data analytics and machine learning processes at scale. The product offers autonomous cloud services with Db2's autonomous self-tuning processing engine, in addition to its fully-automated database monitoring, uptime monitoring, and operations monitoring. Db2 Warehouse on Cloud also includes capabilities for column-based storage, querying compressed datasets, data skipping, and in-memory processing. Finally, Db2 Warehouse on Cloud delivers in-database geospatial data and machine learning features – including algorithms for ANOVA, Association Rule, k-means, Naïve Bayes, Regression analysis, in-database spatial analytics, support for Esri data types, and it natively includes Python drivers and a Db2 Python integration for Jupyter Notebooks. To access these and other features, you can deploy Db2 Warehouse on Cloud via AWS or IBM Cloud.
Db2 BigSQL (formerly known as “IBM SQL”) is a high-performance SQL data engine on Hadoop featuring a Massively Parallel Processing (MPP) architecture. Also known as “Big SQL,” this highly-scalable data engine offers ease and security while querying data from multiple sources across your enterprise. Big SQL can rapidly query data from the widest variety of sources such as RDBMS, HDFS, WebHDFS, object stores, and NoSQL databases. As a hybrid ANSI-compliant SQL engine, Big SQL is highly performant when running queries on unstructured streaming data. Finally, Big SQL is compatible with the entire suite of Db2 products, in addition to the IBM Integrated Analytics System.
Db2 Event Store is a data management system optimized for storing and analyzing high-speed, high-volume, streaming data. Use-cases for Db2 Event Store include Internet of Things (IoT) networks, financial services systems, telecommunications networks, industrial systems, and online retail business systems. The solution offers high-speed analytics and data capture features that allow you to save and analyze up to 250 billion event records daily using only three server nodes. Db2 Event Store integrates IBM Watson Studio technology to support artificial intelligence and machine learning analyses. The solution was also built on Spark, so it works with Spark SQL, Spark Machine Learning, and other compatible tools. Finally, Db2 Event Store supports Go, ODBC, JDBC, Python, and other languages.
Track the content of conversations and who is involved in them. This can be used to generate data about which topics customers are most concerned with so that you can further focus your support efforts accordingly.
Sort specific groups of users and companies that you are communicating with by creating an easily searchable tag that permeates all of your intercom databases, and you can use that tag to integrate other data about those groups throughout intercom.
Collect valuable customer data for your CRM, including basic contact info such as name, email address, and phone number but also more specific data, such as when they signed up, last signed in, and the tags associated with them.
Track the progress of your business relationship with companies (including a list of their users). Use that data to monitor how well your support network is meeting a company’s needs and how much of your overall revenue comes from each of the companies that are interacting with your business via intercom.
Automatically categorize users based on set criteria. Then Intercom can assign support teams based on that criteria, which allows you to more easily match customers with the support team members that can best assist them.