Integrate IBM DB2 with UserVoice
About IBM DB2
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 Xplenty’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.
UserVoice offers product developers a single interface that collects and analyzes customer feedback from a variety of sources. This gives product makers clear, actionable insights into how to improve their offerings. UserVoice eliminates the need to send out surveys, log emails, and search through message boards when trying to understand customer experiences. When a customer reports a complaint or submits an enhancement request through UserVoice, the customer stays in the loop with updates on how their submission is being considered and resolved. This boosts customer engagement and willingness to provide feedback and ideas for product improvement in the future.
Popular Use Cases
Bring all your UserVoice data to Amazon Redshift
Load your UserVoice data to Google BigQuery
ETL all your UserVoice data to Snowflake
Move your UserVoice data to MySQL
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IBM DB2's End Points
IBM Db2 Database
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.
IBM Db2 on Cloud (IBM Db2 Hosted)
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.
IBM Db2 Warehouse
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.
IBM Db2 Warehouse on Cloud (dashbDB for Analytics)
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.
IBM Db2 BigSQL (IBM SQL)
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
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.
UserVoice's End Points
UserVoice Turnkey Install-less Feedback
UserVoice includes a custom-brandable, stand-alone web portal, where your customers can go to provide direct feedback. Users can type in their feedback while receiving auto-suggestions to match their feedback with existing user suggestions. This reduces the chance of feedback duplication and facilitates the surfacing of top ideas. If an issue or enhancement suggestion doesn't exist, users can add a new one. Then, other customers can upvote the suggestion to help you understand the requests to address with the highest priority.
UserVoice In-App Feedback Channel Integration
UserVoice Contributor Sidebar
The Contributor Sidebar is a UserVoice web browser extension that customer-facing teams can use to relay the feedback they capture while interacting with customers. Instead of needing to send an email or drop a post-it note off on a manager's desk, sales associates and customer-facing reps can submit feedback and ideas about enhancement requests and areas for product improvements into the UserVoice system. The Contributor Sidebar browser extension also allows sales teams to connect the feedback they send to an actual customer, who will receive email updates on the status of his or her enhancement request. The sidebar also keeps customer-facing teams in the loop on new developments and progress so they can communicate news to the customers they interact with.
UserVoice Metrics on Product Improvement Opportunities
UserVoice analyzes and groups incoming feedback into easy-to-understand product improvement suggestions, so development teams can understand the number of customers requesting the same improvements. Through visual metrics, graphs, and charts, UserVoice presents valuable information, such as the revenue represented by the customers making specific enhancement requests and how many users want those improvements. This empowers development teams to prioritize the most valuable improvement opportunities.