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.
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PathSolutions TotalView
TotalView offers network monitoring as well as root-cause troubleshooting of problems in plain-English. The solution monitors every device as well as every interface on every device. In addition, TotalView goes deep, collecting 19 error counters, performance, configuration, and connectedness so nothing is outside of it’s view. A built-in heuristics engine analyzes this information to produce plain-English answers to problems. Complex problems can now be solved by junior level engineers leaving the senior level engineers to work on more strategic level projects. The core product includes everything needed to run a perfectly healthy network: Configuration management, server monitoring, cloud service monitoring, IPAM, NetFlow, path mapping, and diagramming. Get Total Network Visibility on your network and solve more problems faster.
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Excelmatic
Excelmatic serves as an AI-driven partner for Excel users, converting unrefined spreadsheets into immediate insights, analytics, and visual representations through an intuitive conversational interface. By simply uploading their files and posing questions in everyday language, users can obtain real-time responses, visual data representations, and KPI overviews without needing to craft any formulas themselves. In the background, Excelmatic streamlines data preparation by tackling the cleaning of intricate tables with tailored rules, smart type identification, and batch processing capabilities. It also employs sophisticated statistical techniques such as trend analysis, anomaly detection, and multi-dimensional breakdowns, producing polished charts like bar, line, and pie graphs that can be dynamically updated and styled. Moreover, its formula assistant enhances productivity by translating plain-English queries into precise functions, providing a comprehensive library, offering suggestions for error correction, and accommodating nested or array formulas. Users can also benefit from the added feature of extracting tabular data with just a single click, making their experience even more efficient. This seamless integration of capabilities positions Excelmatic as an essential tool for anyone looking to maximize their use of Excel.
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RemoteAware GenAI Analytics Platform
The RemoteAware™ GenAI Analytics Platform for IoT revolutionizes the interpretation of intricate sensor and device data streams by delivering clear and actionable insights through cutting-edge generative AI techniques. This platform is capable of ingesting and normalizing massive volumes of diverse IoT data sourced from edge gateways, cloud APIs, or remote assets, utilizing scalable AI pipelines to identify anomalies, predict equipment malfunctions, and produce prescriptive recommendations articulated in straightforward narratives. With a cohesive, web-based dashboard, users benefit from immediate access to crucial performance metrics, customizable alerts, and notifications based on set thresholds, along with the ability to dynamically drill down for time-series analysis. Additionally, the platform's generative summary reports distill extensive datasets into succinct operational briefs, while its capabilities in root-cause analysis and what-if simulations support proactive maintenance and optimal resource distribution. Ultimately, this platform empowers organizations to make data-driven decisions efficiently and effectively.
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