DataBuck
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
Learn more
Curtain LogTrace File Activity Monitoring
In the daily work environment, companies often need to authorize their employees to access and use sensitive company data. However, most companies lack visibility into how their employees are actually utilizing this data, and whether any misuse is occurring. At the same time, companies have to meet internal audit requirements and comply with various data security regulations and policies. This creates a need for the IT department to find ways to effectively monitor and record how employees are accessing and using the company’s data resources.
Curtain LogTrace provides enterprise-wide file activity monitoring. It tracks user actions: create, copy, move, delete, rename, print, open, close, save. Includes source/destination paths and disk type. Perfect for monitoring user file activities.
Key Features:
- File log (create & delete file)
- File log (copy & move file)
- File log (print & rename file)
- App log (save, open & close file)
- Support MySQL & MS SQL
- Watermark for printout
- Central administration
- Integration with Active Directory
- Uninstall password for client
- Password management
- Admin delegation
- Self protection for the software
Learn more
Tenzir
Tenzir is a specialized data pipeline engine tailored for security teams, streamlining the processes of collecting, transforming, enriching, and routing security data throughout its entire lifecycle. It allows users to efficiently aggregate information from multiple sources, convert unstructured data into structured formats, and adjust it as necessary. By optimizing data volume and lowering costs, Tenzir also supports alignment with standardized schemas such as OCSF, ASIM, and ECS. Additionally, it guarantees compliance through features like data anonymization and enhances data by incorporating context from threats, assets, and vulnerabilities. With capabilities for real-time detection, it stores data in an efficient Parquet format within object storage systems. Users are empowered to quickly search for and retrieve essential data, as well as to reactivate dormant data into operational status. The design of Tenzir emphasizes flexibility, enabling deployment as code and seamless integration into pre-existing workflows, ultimately seeking to cut SIEM expenses while providing comprehensive control over data management. This approach not only enhances the effectiveness of security operations but also fosters a more streamlined workflow for teams dealing with complex security data.
Learn more
GlassFlow
GlassFlow is an innovative, serverless platform for building event-driven data pipelines, specifically tailored for developers working with Python. It allows users to create real-time data workflows without the complexities associated with traditional infrastructure solutions like Kafka or Flink. Developers can simply write Python functions to specify data transformations, while GlassFlow takes care of the infrastructure, providing benefits such as automatic scaling, low latency, and efficient data retention. The platform seamlessly integrates with a variety of data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, utilizing its Python SDK and managed connectors. With a low-code interface, users can rapidly set up and deploy their data pipelines in a matter of minutes. Additionally, GlassFlow includes functionalities such as serverless function execution, real-time API connections, as well as alerting and reprocessing features. This combination of capabilities makes GlassFlow an ideal choice for Python developers looking to streamline the development and management of event-driven data pipelines, ultimately enhancing their productivity and efficiency. As the data landscape continues to evolve, GlassFlow positions itself as a pivotal tool in simplifying data processing workflows.
Learn more