Best Data Management Software for IBM DataStage

ActiveBatch by Redwood is a centralized workload automation platform, that seamlessly connects and automates processes across critical systems like Informatica, SAP, Oracle, Microsoft and more. Use ActiveBatch's low-code Super REST API adapter, intuitive drag-and-drop workflow designer, over 100 pre-built job steps and connectors, available for on-premises, cloud or hybrid environments. Effortlessly manage your processes and maintain visibility with real-time monitoring and customizable alerts via emails or SMS to ensure SLAs are achieved. Experience unparalleled scalability with Managed Smart Queues, optimizing resources for high-volume workloads and reducing end-to-end process times. ActiveBatch holds ISO 27001 and SOC 2, Type II certifications, encrypted connections, and undergoes regular third-party tests. Benefit from continuous updates and unwavering support from our dedicated Customer Success team, providing 24x7 assistance and on-demand training to ensure your success.

IRI FieldShield® is a powerful and affordable data discovery and de-identification package for masking PII, PHI, PAN and other sensitive data in structured and semi-structured sources. Front-ended in a free Eclipse-based design environment, FieldShield jobs classify, profile, scan, and de-identify data at rest (static masking). Use the FieldShield SDK or proxy-based application to secure data in motion (dynamic data masking). The usual method for masking RDB and other flat files (CSV, Excel, LDIF, COBOL, etc.) is to classify it centrally, search for it globally, and automatically mask it in a consistent way using encryption, pseudonymization, redaction or other functions to preserve realism and referential integrity in production or test environments. Use FieldShield to make test data, nullify breaches, or comply with GDPR. HIPAA. PCI, PDPA, PCI-DSS and other laws. Audit through machine- and human-readable search reports, job logs and re-ID risks scores. Optionally mask data when you map it; FieldShield functions can also run in IRI Voracity ETL and federation, migration, replication, subsetting, and analytic jobs. To mask DB clones run FieldShield in Windocks, Actifio or Commvault. Call it from CI/CD pipelines and apps.

Create, execute, and oversee AI models while enhancing decision-making at scale across any cloud infrastructure. IBM Watson Studio enables you to implement AI seamlessly anywhere as part of the IBM Cloud Pak® for Data, which is the comprehensive data and AI platform from IBM. Collaborate across teams, streamline the management of the AI lifecycle, and hasten the realization of value with a versatile multicloud framework. You can automate the AI lifecycles using ModelOps pipelines and expedite data science development through AutoAI. Whether preparing or constructing models, you have the option to do so visually or programmatically. Deploying and operating models is made simple with one-click integration. Additionally, promote responsible AI governance by ensuring your models are fair and explainable to strengthen business strategies. Leverage open-source frameworks such as PyTorch, TensorFlow, and scikit-learn to enhance your projects. Consolidate development tools, including leading IDEs, Jupyter notebooks, JupyterLab, and command-line interfaces, along with programming languages like Python, R, and Scala. Through the automation of AI lifecycle management, IBM Watson Studio empowers you to build and scale AI solutions with an emphasis on trust and transparency, ultimately leading to improved organizational performance and innovation.

FairCom EDGE makes it easy to integrate sensor and machine data at their source - be that a factory, water treatment facility, oil platform, wind farm, or other industrial site. FairCom EDGE is the first converged IoT/Industrial IoT hub in the world. It unifies messaging and persistence with an all-in one solution. It also offers browser-based administration, configuration, and monitoring. FairCom EDGE supports MQTT, OPC UA and SQL for machine-tomachine (M2M), communication, and HTTP/REST for monitoring and real-time reporting. It constantly retrieves data from sensors and devices with OPC UA support and receives messages from machines with MQTT support. The data is automatically parsed and persisted, and made available via MQTT or SQL.

FairCom DB is ideal to handle large-scale, mission critical core-business applications that demand performance, reliability, and scalability that cannot easily be achieved with other databases. FairCom DB provides predictable high-velocity transactions with big data analytics and massively parallel big-data processing. It provides developers with NoSQL APIs that allow them to process binary data at machine speed. ANSI SQL allows for simple queries and analysis over the same binary data. Verizon is one of the companies that has taken advantage of FairCom DB's flexibility. Verizon recently selected FairCom DB to be its in-memory database for the Verizon Intelligent Network Control Platform Transaction Server Migrating. FairCom DB, an advanced database engine, gives you a Continuum of Control that allows you to achieve unparalleled performance at a low total cost of ownership (TCO). FairCom DB doesn't conform to you. FairCom DB conforms. FairCom DB doesn't force you to conform to the database's limitations.

Organizations are increasingly focused on becoming more data-driven, implementing dashboards, analytics, and data pipelines throughout the contemporary data landscape. However, many organizations face significant challenges with data reliability, which can lead to misguided business decisions and a general mistrust in data that negatively affects their financial performance. Addressing intricate data challenges is often a labor-intensive process that requires collaboration among various teams, all of whom depend on informal knowledge to painstakingly reverse engineer complex data pipelines spanning multiple platforms in order to pinpoint root causes and assess their implications. Pantomath offers a solution as a data pipeline observability and traceability platform designed to streamline data operations. By continuously monitoring datasets and jobs within the enterprise data ecosystem, it provides essential context for complex data pipelines by generating automated cross-platform technical pipeline lineage. This automation not only enhances efficiency but also fosters greater confidence in data-driven decision-making across the organization.