Business Software for Databricks

QuickLaunch Analytics serves as an enterprise data analytics solution that empowers organizations to consolidate disparate data from various sources, such as ERP, CRM, financial, HR, and operational systems, into a cohesive, governed analytics environment, delivering quicker, actionable insights. Instead of constructing an analytics infrastructure from the ground up, it offers a Foundation Pack featuring automated data pipelines, a cloud-native data lakehouse, and Power BI semantic models, enabling seamless integration, cleansing, and governance of raw enterprise data for analytical purposes. Additionally, the platform includes Application Packs that provide pre-built, application-specific intelligence and ready-to-use semantic models customized for systems like JD Edwards, Viewpoint Vista, NetSuite, and Salesforce, effectively translating intricate data structures into easily understandable business metrics and dashboards. As a result, QuickLaunch Analytics significantly reduces the time required to gain insights from several months or years down to just weeks, all while promoting standardized metrics and reports, facilitating cross-application analysis, and enhancing self-service BI capabilities via the use of cutting-edge technologies. This approach not only streamlines data processing but also enables organizations to make data-driven decisions with greater agility and confidence.

Vega is an innovative, AI-native platform for federated security analytics designed to provide security operations teams with comprehensive visibility, detection, investigation, and response capabilities across their security data without the need for expensive data migration or centralized ingestion. Its Security Analytics Mesh (SAM) empowers analysts to effortlessly access and query data regardless of location, including SIEMs, data lakes, cloud services, and cold storage, utilizing natural language or query languages to eliminate blind spots and minimize costs and maintenance while enhancing coverage. The platform offers AI-driven detections, automated triage, and correlation of alerts across various environments, allowing teams to create, deploy, and refine detection rules once and apply them universally. In addition to these benefits, Vega continually optimizes alerts to decrease unnecessary noise, reveals overlooked security vulnerabilities, and seamlessly integrates with existing security ecosystems through a variety of pre-built connectors. With its ability to streamline security operations, Vega stands out as a crucial tool in enhancing organizational security posture.

Simon AI is a marketing platform driven by artificial intelligence, aimed at assisting organizations in leveraging customer data to effortlessly initiate personalized campaigns across various digital platforms. By merging a flexible customer data system with self-sufficient AI agents, it assesses customer behaviors, contextual cues, and business metrics to develop precisely tailored marketing experiences. Rather than having marketing teams manually sort through audience segments or execute intricate queries, Simon AI empowers marketers to establish business objectives, like boosting conversions, reducing churn, or encouraging repeat purchases, while its AI agents take care of data organization, insight extraction, and campaign implementation. Furthermore, it incorporates a variety of information, including customer interactions, transaction history, and contextual variables such as browsing habits, inventory status, weather fluctuations, and social media activity, to facilitate timely and pertinent marketing responses. This innovative approach not only streamlines marketing efforts but also enhances the relevance of customer interactions, ultimately leading to improved business outcomes.

EZConvertBI is an intelligent solution for business intelligence migration that leverages AI to streamline the intricate task of moving dashboards, reports, datasets, and analytics from outdated BI platforms, including Tableau, Qlik, and Power BI, to contemporary, cloud-based environments like Amazon QuickSight, Looker, and Power BI. By utilizing this tool, organizations can achieve migration of BI assets with execution speeds increased by as much as 90% and substantial cost savings, all while ensuring the preservation of visual aesthetics, business logic, SQL queries, extracts, and calculations during the entire process. The solution features an Analyzer component that interfaces with existing BI systems or uploaded workbooks to evaluate complexity, pinpoint duplicate or obsolete dashboards, and produce comprehensive diagnostic reports detailing migration scope, projected costs, and potential impacts. Moreover, its automated conversion engine proficiently maps and transforms dashboards, datasets, and queries into the desired target environment, guaranteeing the maintenance of functionality and the accurate replication of both visuals and underlying logic. This innovative approach not only simplifies the migration process but also empowers businesses to harness the full potential of their data in a modern analytics landscape.

Simtheory is an innovative AI-driven workspace that revolutionizes team collaboration by converting discussions into tangible actions through integrated systems, data, and smart assistants. More than just a chatbot, it provides a secure platform where users can create AI assistants tailored to their business needs, capable of accessing internal resources and performing various tasks like drafting reports, analyzing data, updating CRM entries, scheduling appointments, or communicating with stakeholders. By connecting directly to data warehouses, SaaS applications, and internal infrastructures, the AI gains comprehensive context to produce precise and relevant outputs, empowering teams to evolve from basic prompts to delegated responsibilities with measurable results. Users can also design shared assistants with personalized instructions and knowledge bases, fostering standardized workflows and enhancing collaboration across different projects. Additionally, Simtheory accommodates multiple AI models within a single workspace, enabling users to switch effortlessly between them according to their requirements. This flexibility ensures that teams can adapt to changes and challenges in their work environment more efficiently.

VoxiHost is a Virtual Private Server (VPS) hosting solution that aims to deliver exceptional performance and adaptable infrastructure for applications, websites, and online services within a private cloud setting. With dedicated server resources and complete root access, users can install and control their own operating systems and software stacks, sidestepping the restrictions typically associated with shared hosting. Powered by cutting-edge AMD Ryzen 9 7950X3D processors, along with NVMe SSD storage and DDR5 memory, VoxiHost ensures rapid computing capabilities and minimal data access latency, making it ideal for intensive workloads. The platform accommodates a diverse array of applications, from hosting websites and game servers to managing databases, bots, development environments, and VPNs, providing versatility for both individual users and businesses. Additionally, VoxiHost offers a selection of pre-configured operating system templates, including popular options like Ubuntu, Debian, and Windows Server, which facilitate swift deployment and simplify the onboarding process for less tech-savvy users. This combination of high performance and user-friendliness positions VoxiHost as a robust choice for various hosting needs.

Actian Data Observability is an advanced platform leveraging AI to continuously oversee, validate, and maintain the integrity, quality, and dependability of data within contemporary data environments. This system employs automated Data Observability Agents that assess the data as it enters data lakehouses or warehouses, identifying anomalies, elucidating root causes, and facilitating problem resolution before these issues can affect dashboards, reports, or AI applications. By providing instantaneous visibility into data pipelines, it guarantees that data remains precise, comprehensive, and reliable throughout its entire lifecycle. Unlike traditional methods that depend on sampling, it eradicates blind spots by monitoring the entirety of the data, which empowers organizations to uncover concealed errors that may compromise analytics or machine learning results. Furthermore, its integrated anomaly detection, driven by AI and machine learning technologies, allows for the early identification of irregularities such as changes in schema, loss of data, or unexpected distributions, leading to more rapid diagnosis and resolution of issues. Overall, this innovative approach significantly enhances the organization's ability to trust in their data-driven decisions.

Actian AI Analyst serves as a conversational analytics platform that is context-aware, aimed at empowering organizations to derive reliable insights from their data through natural language interactions. By enabling business users to pose inquiries without the need for SQL, it revolutionizes conventional dashboards into dynamic, ongoing dialogues with data. Before any analysis is performed, it functions on a governed semantic layer that encapsulates business metrics, relationships, and definitions, thereby ensuring that each query aligns with the organization's operational framework. This semantic layer is generated and upheld by the Steward AI agent, which persistently tracks data definitions and their interconnections, offering actionable plans for maintaining accuracy over time. Additionally, AI Analyst retains the conversational context in follow-up questions, facilitating a more profound investigation while ensuring that results remain consistent with established business logic. Its intuitive design fosters a seamless user experience, making data interactions more accessible and insightful for all business users.

The Actian Data Intelligence Platform is a cloud-native, AI-ready solution aimed at revolutionizing the way organizations discover, comprehend, manage, and trust their data in intricate environments. By consolidating features such as data cataloging, metadata oversight, governance, lineage tracking, observability, and semantic context into a cohesive platform, it establishes a centralized and reliable layer for enterprise data management. Leveraging a federated knowledge graph, the platform fosters intelligent connections between data assets, which allows it to inherently grasp context, yield pertinent search outcomes, and suggest optimal data utilization. This innovative strategy empowers both technical and business users to efficiently locate and utilize trustworthy data, thereby enhancing decision-making processes and boosting operational efficiency. Additionally, the platform performs continuous monitoring of data integrity, enforces governance protocols, and produces automated trust indicators, ensuring that data remains accurate, compliant, and primed for analytics along with AI applications. As a result, organizations can confidently navigate their data landscapes and harness the full potential of their information assets.

Singulr is a comprehensive platform designed for enterprise AI governance and security, providing a cohesive control framework that aids organizations in discovering, securing, and optimizing their AI implementations on a large scale. By tackling the widening gap between the rapid deployment of AI technologies and the constraints of governance, it offers unparalleled visibility into all AI systems utilized within the organization, which includes custom applications, integrated AI solutions, public tools, and shadow AI that often evade detection by security teams. It systematically identifies and catalogs AI resources throughout the organization, creating a real-time inventory of agents, models, and services while evaluating their associated risks through thorough contextual assessments of data management, model lineage, vulnerabilities, and compliance requirements. The platform's intelligence layer, Singulr Pulse, processes millions of AI systems, assigns risk ratings, and facilitates automated onboarding processes that significantly shorten approval timelines from weeks to mere hours, all while ensuring robust security measures are in place. This innovative approach not only enhances the efficiency of AI adoption but also empowers organizations to maintain a strong governance framework as they navigate the complexities of AI integration.

Notenic serves as a runtime orchestration and governance platform aimed at managing and securing autonomous AI agents, also known as "digital labor," in real-time scenarios where failures could lead to significant regulatory, legal, or operational repercussions. Functioning as an infrastructure layer, it integrates directly into the execution path of AI systems to enforce strict governance protocols prior to any interaction with systems of record, thus avoiding the limitations of post-output filters or controls applied at the prompt level. The platform incorporates a zero-trust runtime architecture characterized by foundational principles such as zero-persistence, which ensures no data is retained after each session, and execution-path control that enforces policies right at the moment actions are taken. This design also emphasizes independence from model context, effectively preventing any adversarial inputs from compromising governed behavior. In addition, Notenic offers a comprehensive control plane that encompasses the management of AI agents, treating them as operational units with clearly defined roles and appropriate oversight, which enhances organizational efficiency and accountability. This robust framework ultimately ensures that AI operations are conducted within a secure and compliant environment.

Matters.AI stands out as the pioneering AI Security Engineer for Data, specifically designed to autonomously detect, comprehend, and address instances of data misuse before any ticket is generated by the Security Operations Center (SOC). This innovative solution safeguards what truly matters, overseeing sensitive data as it exists or moves across various platforms, functioning similarly to a human security engineer that comprehends context, monitors activities, and protects sensitive information independently across environments such as cloud services, SaaS, endpoints, microservices, and AI pipelines. Built upon advanced technologies like semantic intelligence, nearest neighbor search, data lineage modeling, and predictive behavior analysis, Matters goes beyond mere threat detection; it interprets context, foresees potential risks, and takes proactive measures. Rather than depending on outdated static rules, regex patterns, cumbersome dashboards, and incessant alerts, Matters adeptly reads nuanced data signals, tracks risks in real-time, and operates around the clock. By identifying sensitive data based not solely on appearance but also on its significance, Matters employs techniques like fingerprinting and eBPF to monitor data across cloud environments, SaaS applications, endpoints, and beyond, ensuring comprehensive protection and awareness. In this way, Matters.AI not only enhances data security but also transforms the landscape of risk management in the digital age.

SAS Studio offers a programming environment accessible through web browsers, making it simpler and quicker to write and engage with SAS code from any location. This platform is designed to enhance teamwork by facilitating the creation of effective data pipelines, promoting effortless collaboration, minimizing the need for extensive coding, and allowing for open-source integration. It interfaces with prominent cloud data services like AWS Redshift and S3, Google BigQuery and Cloud Storage, and Azure Data Lake Storage, in addition to various relational and non-relational databases such as Oracle, Snowflake, Teradata, SingleStore, and MongoDB. Furthermore, SAS Studio is compatible with multiple file formats, including Excel, text, Parquet, and ORC. Users have the flexibility to work with a no-code, low-code, or traditional coding approach, enabling them to construct comprehensive data pipelines through drag-and-drop operations, create Python and SAS code within SAS Studio or other IDEs, and integrate these components into SAS Studio workflows for secure and centralized data access. Additionally, SAS Studio accommodates both ELT and ETL methodologies, ensuring versatility in data handling. This adaptability makes SAS Studio a valuable tool for data professionals aiming to streamline their analytics processes.

Fig enhances Security Operations Resilience for contemporary SOC teams, empowering them to endure transformations without succumbing to disruptions. While change can jeopardize a SOC's functionality, it can also serve as a source of strength, and Fig ensures that both detection and response mechanisms remain operational during instances of drift and intentional modifications. Drift occurs when alterations from upstream sources inadvertently disrupt detection protocols and automations, leaving teams without alerts or guidance and potentially facing lengthy and arduous processes to identify and rectify issues. In addition, planned changes, such as enhancements in SecOps and infrastructure initiatives, often progress at a cautious pace to prevent any adverse effects on production systems. To address these challenges, Fig equips teams with drift detection tools that identify when a detection or response fails, drift repair capabilities that pinpoint the underlying cause, recommend solutions, conduct tests, and facilitate deployment upon approval, along with change modeling features that allow teams to simulate proposed initiatives and evaluate their potential consequences prior to implementation in production. This comprehensive approach ensures that SOC teams can navigate the complexities of change with confidence and efficiency.

Zingg is an open-source platform designed for Master Data Management, tailored for contemporary data warehousing needs. By leveraging machine learning for scalable entity resolution, it removes the reliance on costly and inflexible MDM solutions. Seamlessly integrated with Databricks, Microsoft Fabric, Snowflake, AWS, and GCP, Zingg empowers data teams to create a cohesive and reliable view of customers, suppliers, and products directly within their existing data environments. With a persistent Zingg ID, golden records are consistently upheld across various systems and data sources, ensuring data integrity and accessibility. Moreover, Zingg's innovative approach simplifies the management of master data, allowing organizations to focus on data-driven decision-making.

WhereScape is a tool that helps IT organizations of any size to use automation to build, deploy, manage, and maintain data infrastructure faster. WhereScape automation is trusted by more than 700 customers around the world to eliminate repetitive, time-consuming tasks such as hand-coding and other tedious aspects of data infrastructure projects. This allows data warehouses, vaults and lakes to be delivered in days or weeks, rather than months or years.

Soda helps you manage your data operations by identifying issues and alerting the right people. No data, or people, are ever left behind with automated and self-serve monitoring capabilities. You can quickly get ahead of data issues by providing full observability across all your data workloads. Data teams can discover data issues that automation won't. Self-service capabilities provide the wide coverage data monitoring requires. Alert the right people at just the right time to help business teams diagnose, prioritize, fix, and resolve data problems. Your data will never leave your private cloud with Soda. Soda monitors your data at source and stores only metadata in your cloud.

Talend Data Catalog provides your organization with a single point of control for all your data. Data Catalog provides robust tools for search, discovery, and connectors that allow you to extract metadata from almost any data source. It makes it easy to manage your data pipelines, protect your data, and accelerate your ETL process. Data Catalog automatically crawls, profiles and links all your metadata. Data Catalog automatically documents up to 80% of the data associated with it. Smart relationships and machine learning keep the data current and up-to-date, ensuring that the user has the most recent data. Data governance can be made a team sport by providing a single point of control that allows you to collaborate to improve data accessibility and accuracy. With intelligent data lineage tracking and compliance tracking, you can support data privacy and regulatory compliance.

You've spent years building up your business. Don't let cyber criminals destroy that in seconds. REDXRAY's proprietary intelligence feeds can identify threats daily against your networks, target companies/agencies, or supply chain. The emailed threat report covers the following types of threats: Botnet Tracker (also known as Botnet Tracker), Breach Data (also known as Breach Data), Keylogger Records (also known as Keylogger Records), Malicious Emails Context and Malicious Email Detections), OSINT Records, Sinkhole Traffic and THREATRECON Records.

AppScope introduces a revolutionary method for black-box instrumentation, providing comprehensive and consistent telemetry from any Linux executable simply by adding scope before the command. When you engage with customers who utilize Application Performance Management, they often express their satisfaction with the solution but lament the limited extension to additional applications. Typically, only a small fraction—10% or less—of their applications are equipped with APM, while they rely on basic metrics for the remainder. This raises the question: what happens to the other 80%? This is where AppScope comes into play. It eliminates the need for language-specific instrumentation and does not require input from application developers. As a language-agnostic tool that operates entirely in userland, AppScope can be utilized with any application and seamlessly scales from command-line interfaces to production environments. Users can channel AppScope data into any pre-existing monitoring tool, time-series database, or logging solution. Furthermore, AppScope empowers Site Reliability Engineers and Operations teams to closely analyze live applications, providing insights into their functionality and performance across various deployment environments, whether on-premises, in the cloud, or within containerized systems. This capability not only enhances monitoring but also fosters a deeper understanding of application behavior, paving the way for improved performance management.

Corelight offers the advantages of Zeek without the complications associated with Linux, network interface card issues, or the risk of packet loss. Setting it up is a matter of minutes rather than an extensive timeline, allowing your skilled personnel to focus on threat hunting instead of resolving technical glitches. This robust platform, rooted in open-source technology, provides you with full access to your metadata, enabling customization and extension of your capabilities, all while being part of an engaging community. We have assembled a top-tier team of Zeek specialists and contributors, supported by a world-class customer care team that consistently impresses clients with their exceptional expertise and quick response times. With the proactive and secure Corelight Dynamic Health Check feature activated, your Corelight Sensor transmits performance data back to Corelight, allowing for the early detection of potential issues like disk failures or unusual performance metrics. This ensures that your network remains secure and operationally efficient at all times. Ultimately, Corelight empowers organizations to safeguard their networks with confidence and efficiency.

Monad serves as a comprehensive security data cloud platform that simplifies the processes of extracting, transforming, and loading (ETL) data from a variety of security tools into a cohesive data warehouse. This platform empowers security teams to efficiently export data from their existing tools, customize it into tailored data models, and seamlessly deliver it to their data warehouses, thereby enabling smooth integration and deeper analysis. Additionally, it provides capabilities for security, DevOps, and cloud engineering teams to engage with data using SQL and business intelligence tools, which improves their effectiveness in normalizing, transforming, and enriching data to enhance security and compliance results. With its intuitive interface and robust enterprise-grade connectors, Monad makes it easy to establish a security data lake, assisting organizations in breaking down data silos and gaining valuable insights and analytics that contribute to effective security management. The ability to unify disparate data sources fosters a more holistic view of security metrics, ultimately leading to more informed decision-making and proactive risk management.

Create continuously improving predictive models effortlessly, without the need for intricate engineering processes. Seamlessly integrate with your current cloud data warehouse, utilizing all available data in its existing location. Effortlessly share features and deploy advanced machine learning models using just SQL or dbt, or expand functionality with Python if needed. Keep predictions organized within your data warehouse for straightforward access by your business intelligence and operational systems. Manage features and predictions directly in your data warehouse, eliminating the need for additional infrastructure. Construct cutting-edge models that capitalize on all your data without the necessity of writing code or establishing pipelines. Foster collaboration between analytics and AI teams through the comprehensive extensibility of Continual's declarative AI framework. Oversee features, models, and policies using a declarative GitOps workflow as your operations expand. Enhance the speed of model development with a collaborative feature store and a data-centric approach, while also ensuring cross-team communication remains seamless. This innovative approach allows for a more integrated and efficient workflow, ultimately driving better insights and outcomes.

Creating AI solutions necessitates a robust engineering strategy that emphasizes resilience, openness, and repeatability to attain the required quality and agility. Up until now, these initiatives have lacked a solid foundation to tackle these issues amidst a multitude of specialized tools and the rapidly evolving landscape of models and data. A collaborative development platform is essential for automating the creation and management of AI applications that cater to various user roles. By extracting highly detailed customer profiles from organizational data, businesses can forecast behaviors in real-time and on a large scale. AI-driven models can be generated to facilitate continuous learning and to meet specific business objectives. This approach also allows organizations to clarify and demonstrate their compliance with relevant laws and regulations. CognitiveScale's Cortex AI Platform effectively addresses enterprise AI needs through a range of modular offerings. Customers can utilize and integrate its functionalities as microservices within their broader AI strategies, enhancing flexibility and responsiveness to their unique challenges. This comprehensive framework supports the ongoing evolution of AI development, ensuring that organizations can adapt to future demands.

WisdomAI is a cutting-edge analytics platform that harnesses the power of AI to deliver instant insights across all data, whether structured or unstructured. Users can interact with the platform by asking simple, plain-language questions and get actionable answers instantly, enabling faster decision-making. The platform's knowledge fabric unifies data, offering a holistic view that breaks down silos and helps teams collaborate more effectively. WisdomAI also uncovers trends and opportunities proactively, delivering recommendations that are specifically tailored to each user’s goals. With seamless integration into BI tools and enterprise systems, it ensures that users have real-time access to insights. The platform’s enterprise-grade security, along with granular access controls and compliance certifications, guarantees safe and secure AI adoption across the organization.