Best Data Management Software in Asia - Page 72

ThinkData Works provides a robust catalog platform for discovering, managing, and sharing data from both internal and external sources. Enrichment solutions combine partner data with your existing datasets to produce uniquely valuable assets that can be shared across your entire organization. The ThinkData Works platform and enrichment solutions make data teams more efficient, improve project outcomes, replace multiple existing tech solutions, and provide you with a competitive advantage.

Launch a backend in under two minutes by starting with a Postgres database that includes features like authentication, instant APIs, real-time subscriptions, and storage capabilities. Accelerate your development process and direct your efforts toward enhancing your products. Each project utilizes a complete Postgres database, recognized globally as a reliable relational database. Implement user sign-ups and logins while ensuring data security through Row Level Security measures. Facilitate the storage, organization, and serving of large files, accommodating various media types such as videos and images. Customize your code and set up cron jobs seamlessly without the need to deploy or manage scaling servers. There are numerous example applications and starter projects available to help you get started quickly. The platform automatically introspects your database to generate APIs instantly, allowing you to avoid the tedious task of creating repetitive CRUD endpoints and concentrate on your product's development. Type definitions are automatically created from your database schema, enabling a more streamlined coding experience. You can also use Supabase directly in your browser without a complicated build process, and develop locally before deploying to production at your convenience. Manage your Supabase projects effectively right from your local machine, ensuring a smooth and efficient workflow throughout your development journey.

Dockit Metadata Manager allows you to manage all aspects of metadata management within SharePoint. SharePoint content without proper metadata is a storage repository that SharePoint users can access. This results in poor user adoption and under-utilization of SharePoint's powerful capabilities. No matter if you have an established SharePoint environment that is in production or are just beginning to organize your SharePoint metadata, you must have complete control over how it is organized and managed. Find your SharePoint metadata across different elements like sites, lists, libraries, etc. Before you migrate to SharePoint, discover the metadata in your file shares or folders. To further improve your metadata, you must first identify what is there.

Transform your big data processes and create intelligent knowledge repositories with the Data Lake Governance Center (DGC), a comprehensive platform for managing all facets of data lake operations, including design, development, integration, quality, and asset management. With its intuitive visual interface, you can establish a robust data lake governance framework that enhances the efficiency of your data lifecycle management. Leverage analytics and metrics to uphold strong governance throughout your organization, while also defining and tracking data standards with the ability to receive real-time alerts. Accelerate the development of data lakes by easily configuring data integrations, models, and cleansing protocols to facilitate the identification of trustworthy data sources. Enhance the overall business value derived from your data assets. DGC enables the creation of tailored solutions for various applications, such as smart government, smart taxation, and smart campuses, while providing valuable insights into sensitive information across your organization. Additionally, DGC empowers businesses to establish comprehensive catalogs, classifications, and terminologies for their data. This holistic approach ensures that data governance is not just a task, but a core aspect of your enterprise's strategy.

Smartlogic's Semaphore, a cutting-edge Semantic AI platform, uncovers qualified contextual data through a centralized integrated system that effectively identifies enterprise information and facilitates the creation and management of semantic and active metadata, as well as information extraction. This powerful tool serves as a foundation for cognitive applications, enabling intelligent contextual searches, enhancing process automation, providing relevant recommendations, improving customer experiences, ensuring regulatory compliance, managing contract lifecycles, and bolstering information security. By leveraging Semaphore, organizations can drive impactful marketing efforts, boost revenue, and enhance customer satisfaction while streamlining operational efficiency and mitigating risks. The platform empowers businesses to bridge the gap between their language and that of their customers, ensuring timely access to the right information for support. Furthermore, it helps close compliance gaps, enforces governance best practices, and lowers costs through transparent and traceable outcomes, ultimately leading to a more informed and agile organization. Adopting Semaphore not only improves operational workflows but also fosters a culture of accountability and continuous improvement.

MetaCenter allows both business and technology departments to systematically organize and categorize the information resources of an organization. Through this platform, users can independently inquire about their data assets and understand the movement of data within the business, as well as determine the appropriate usage classifications. This capability helps organizations minimize expenses while enhancing flexibility and mitigating operational risks. The search-based semantic layer facilitates the automatic cross-referencing of models. Additionally, tailored Faceted Views for specific data assets can be made accessible to distinct roles within the organization. The lower total cost of ownership combined with increased automation results in a superior return on investment when compared to rival solutions. Moreover, the intuitive, GUI-driven customization allows for quick application adaptations without the need for programming expertise or professional services, making it highly user-friendly. Ultimately, this empowers teams to respond swiftly to changing business needs and enhances overall productivity.

SAS Visual Statistics allows for collaborative data exploration among multiple users, enabling them to interactively develop and refine predictive models. Data scientists and statisticians can leverage the most suitable analytical techniques to act on insights at a detailed level. Consequently, you will discover insights at remarkable speeds, uncovering new opportunities for revenue growth. The platform facilitates the construction and fine-tuning of models aimed at specific demographics or segments while simultaneously running various scenarios. This capability encourages users to pose numerous what-if questions to enhance outcomes. Additionally, results can be operationalized through automatically generated score code. Users are empowered to visually manipulate data by adding or adjusting variables, eliminating outliers, and more. Changes can be instantly assessed for their impact on the model's predictive accuracy, allowing for swift adjustments. Data science teams enjoy the ultimate flexibility by working in their preferred programming languages, maximizing their expertise. Ultimately, SAS Visual Statistics integrates all analytical resources, making it a comprehensive solution for data-driven decision-making. It fosters an environment where innovation can thrive, pushing the boundaries of what data analysis can achieve.

SAS® Viya® offers a robust and scalable analytics platform that is both efficient and easy to implement, allowing organizations to address a variety of business challenges. The insights generated automatically help in pinpointing the most frequently used variables across all models, highlighting key variables selected along with evaluation outcomes for each model. With the integration of natural language generation, project summaries are produced in straightforward language, which simplifies the interpretation of reports for users. Moreover, members of the analytics team can enhance the insights report with project notes, promoting better communication and teamwork. SAS further enables the integration of open source code within analyses, allowing users to utilize open source algorithms effortlessly in its platform. This flexibility encourages collaboration throughout your organization, as users are free to program in their preferred language. Additionally, you can leverage SAS Deep Learning with Python (DLPy), an open-source package available on GitHub, to expand your analytical capabilities even further. By using these tools, businesses can significantly enhance their data-driven decision-making processes.

Utilize a robust suite of SAS technologies to access, manipulate, analyze, and present information through visual formats. By leveraging SAS Visual Machine Learning, organizations can enhance their analytical capabilities with integrated machine learning and deep learning features, which facilitate improved visualization and reporting practices. This approach allows users to visualize and uncover pertinent relationships within their data. Additionally, the platform supports the creation and sharing of interactive reports and dashboards, alongside enabling self-service analytics to swiftly evaluate potential outcomes, fostering smarter, data-driven decisions. Users can delve into their data and construct or modify predictive analytical models while operating within the SAS® Viya® environment. Collaborative efforts among data scientists, statisticians, and analysts enable iterative model refinement tailored to specific segments or groups, ensuring decisions are informed by precise insights. Moreover, this comprehensive visual interface simplifies the resolution of intricate analytical challenges, efficiently managing every aspect of the analytics lifecycle while promoting a more collaborative environment for all stakeholders involved.

Access, analyze, and manipulate data to uncover emerging trends and patterns effectively. SAS Visual Data Science provides a unified, self-service platform that enables the creation and sharing of intelligent visualizations alongside interactive reports. Leveraging machine learning, text analytics, and econometric techniques enhances forecasting and optimization capabilities, while also allowing for the management and registration of both SAS and open-source models, whether within projects or as independent entities. Utilize this tool to visualize and identify pertinent relationships within your data. Generate and disseminate interactive reports and dashboards, employing self-service analytics to promptly evaluate potential outcomes for more informed, data-driven decisions. Dive into data exploration and construct or modify predictive analytical models using this solution integrated with SAS® Viya®. By fostering collaboration among data scientists, statisticians, and analysts, teams can iteratively refine models tailored to specific segments or groups, thereby empowering decisions rooted in precise insights. This collaborative approach not only enhances model accuracy but also accelerates the decision-making process significantly.

Develop, implement, and manage data-driven decision-making processes on a large scale in either real-time or batch modes. SAS Data Science Programming caters to data scientists who prefer a purely programmatic method, allowing them to utilize SAS's analytical tools throughout the entire analytics life cycle, which encompasses data preparation, exploration, and deployment. Uncover and visualize significant patterns within your datasets, enabling the creation and dissemination of interactive reports and dashboards. Additionally, leverage self-service analytics to swiftly evaluate likely outcomes, leading to more informed and data-centric decisions. Engage with your data and create or modify predictive analytical models using the SAS® Viya® platform. This collaborative environment empowers data scientists, statisticians, and analysts to work together, refining their models iteratively for various segments, ultimately supporting decision-making based on reliable insights. Tackle intricate analytical challenges through an all-encompassing visual interface that efficiently manages every aspect of the analytics life cycle, ensuring that users can navigate complexities with ease and precision. By embracing this approach, organizations can enhance their strategic decision-making capabilities significantly.

Incorporate analytics into immediate interactions and event-driven functionalities. The SAS Visual Data Science Decisioning suite offers strong capabilities in data management, visualization, advanced analytics, and model oversight. It enhances decision-making by crafting, integrating, and governing analytically driven decision processes at scale, whether in real-time or through batch processing. Additionally, it facilitates analytics deployment in the data stream to uncover valuable insights. Tackle intricate analytical challenges with an intuitive visual interface that manages all stages of the analytics life cycle efficiently. Running on SAS® Viya®, SAS Visual Data Mining and Machine Learning merges data manipulation, exploration, feature development, and cutting-edge statistical, data mining, and machine learning methodologies within a single, scalable in-memory processing framework. Users can access data files, libraries, and existing scripts, or create new ones, via this web-based application that is conveniently accessible through any browser, thus enhancing flexibility and collaboration.

Introducing a user-friendly yet robust suite designed for accessing, manipulating, analyzing, and showcasing data, now offered for both cloud-based and on-premises solutions. Why struggle with disparate software tools from various providers? A unified collection that features three of our most sought-after products—Base SAS, SAS/STAT, and SAS/GRAPH—minimizes expenses related to licensing, maintenance, training, and support, all while ensuring uniform access to information throughout your organization. Our SAS statistical methods are regularly updated to incorporate the latest developments in statistical science. Additionally, our technical support team consists of seasoned statisticians with master's and doctorate degrees, providing a level of expertise and service that is rare among software vendors. With over forty years of experience in crafting statistical analysis tools, SAS continues to be the trusted choice for organizations globally seeking reliable solutions for their data inquiries. This commitment to excellence ensures that you are well-equipped to make informed decisions based on accurate data insights.

Uncover the hidden order within your intricate data landscape and consistently know where to seek solutions. Datakin seamlessly tracks data lineage, presenting your entire data ecosystem through an engaging visual graph. This visualization effectively highlights the upstream and downstream connections associated with each dataset. The Duration tab provides an overview of a job’s performance in a Gantt-style chart, complemented by its upstream dependencies, which simplifies the identification of potential bottlenecks. When it's essential to determine the precise moment a breaking change occurs, the Compare tab allows you to observe how your jobs and datasets have evolved between different runs. Occasionally, jobs that complete successfully may yield poor output. The Quality tab reveals crucial data quality metrics and their fluctuations over time, making anomalies starkly apparent. By facilitating the swift identification of root causes for issues, Datakin also plays a vital role in preventing future complications from arising. This proactive approach ensures that your data remains reliable and efficient in supporting your business needs.

Out of control unstructured data volumes have made your work environment a messy and costly data swamp, where you can't trust or find the files you need. Panzura transforms your storage into the most secure and user-friendly cloud data management platform in the world. You can achieve global data consistency and immediate, efficient performance at scale. Secure data access from the edge to the core to the cloud without any performance penalties. You can create a collaborative work environment that is accessible from anywhere. Cloud mirroring and multi-cloud redundancy provide data protection and data protection. If you are overwhelmed by data, innovation can seem impossible. Panzura consolidates and simplifies your data management, increasing visibility and access, encouraging collaboration and allowing you to achieve better outcomes in less time.

HPE Cloud Volumes addresses the requirements for enterprise data protection and offers Hybrid and Multi-Cloud Storage Services tailored for modern businesses. These services seamlessly support a range of migration strategies, whether moving data from edge locations, on-premises environments, or across various cloud platforms. Users can enjoy the benefits of cloud-like agility, scalability, and innovation, complemented by robust security measures, quick deployment, and flexible pay-as-you-go pricing models. Specifically, HPE Cloud Volumes Backup acts as a cloud backup solution designed for edge, on-premises, and cloud workloads, streamlining your data protection efforts with simplicity, efficiency, and enhanced reliability. This service provides a genuine cloud experience, allowing for direct backups from any storage array or backup ISV, eliminating the need for additional hardware appliances. Meanwhile, HPE Cloud Volumes Block offers a hybrid and multi-cloud storage solution that enables dynamic attachment of data to various cloud computing providers, ensuring freedom from vendor lock-in and avoiding egress fees. This versatile service is ideal for various applications, including disaster recovery, hybrid continuous integration and deployment, bi-directional migrations, and comprehensive hybrid data protection strategies. The combination of these services empowers organizations to maximize their operational efficiency while ensuring secure and reliable data management.

Transform your data into a real-time stream, ensuring it is instantly accessible and ready for utilization. Leo simplifies the complexities of event sourcing, allowing you to effortlessly create, visualize, monitor, and sustain your data streams. By unlocking your data, you free yourself from the limitations imposed by outdated systems. The significant reduction in development time leads to higher satisfaction among both developers and stakeholders alike. Embrace microservice architectures to foster continuous innovation and enhance your agility. Ultimately, achieving success with microservices hinges on effective data management. Organizations need to build a dependable and repeatable data backbone to turn microservices into a tangible reality. You can also integrate comprehensive search functionality into your custom application, as the continuous flow of data makes managing and updating a search database a seamless task. With these advancements, your organization will be well-positioned to leverage data more effectively than ever before.

Analyzing time-series data is crucial for the daily functions of numerous businesses. Common applications involve assessing consumer foot traffic and conversion rates for retailers, identifying anomalies in data, discovering real-time correlations within sensor information, and producing accurate recommendations. With the Cloud Inference API Alpha, businesses can derive real-time insights from their time-series datasets that they input. This tool provides comprehensive details about API query results, including the various groups of events analyzed, the total number of event groups, and the baseline probability associated with each event returned. It enables real-time streaming of data, facilitating the computation of correlations as events occur. Leveraging Google Cloud’s robust infrastructure and a comprehensive security strategy that has been fine-tuned over 15 years through various consumer applications ensures reliability. The Cloud Inference API is seamlessly integrated with Google Cloud Storage services, enhancing its functionality and user experience. This integration allows for more efficient data handling and analysis, positioning businesses to make informed decisions faster.

Transform the way your workforce engages with data from historians, SCADA, and IoT devices, tailoring insights for everyone from field personnel to data analysts. Dive into your data like never before with a comprehensive platform that allows for integration, organization, collaboration, and visualization of industrial information all in one place. Effortlessly navigate and visualize numerous data signals simultaneously while maintaining clarity and performance through our innovative streaming data timeline technology. Initiate discussions or report incidents by tagging team members directly within the data timeline, enhancing communication and context by including media such as images and videos. Access historical activities to prevent redundant problem-solving, ensuring efficiency in your operations. Our robust permission system guarantees that your data remains accessible solely to you, while developer-friendly documentation and secure APIs facilitate safe and straightforward interactions. Whether you are at your desk, on a tablet, or using a mobile phone, our platform is optimized for all modern browsers, and you can also carry industrial data with you wherever you go through our dedicated mobile applications. This approach not only streamlines operations but also fosters a culture of continuous learning and collaboration among your teams.

Every event, from transactions to meetings, occurs at a specific moment or over a span of time, making it essential for successful investigations to grasp the sequence and connections of these events. KronoGraph stands out as the pioneering toolkit designed for scalable timeline visualizations that uncover trends within temporal data. Create engaging timeline tools that allow for the exploration of how events and relationships progress over time. Whether you're examining communication between two individuals or analyzing IT traffic across an entire enterprise, KronoGraph delivers a comprehensive and interactive representation of the information. The tool enables a seamless transition from a broad overview to detailed individual occurrences, enhancing the investigative process as it develops. Often, investigations hinge on pinpointing critical elements like a person, an event, or a connection. With the dynamic interface of KronoGraph, you can navigate through time, revealing anomalies and trends while zooming in on specific entities that elucidate the deeper narrative contained within your data. This capability not only simplifies complex analyses but also empowers users to draw insights that would otherwise remain obscured.

Create revolutionary graph visualization solutions that transform interconnected data into valuable insights. Utilize the versatility and strength of JavaScript to swiftly develop graph visualization applications that are accessible to anyone, anywhere. KeyLines offers a fully adaptable approach to constructing your graph visualization application. Design interactive tools that uncover hidden insights and potential threats. The KeyLines JavaScript toolkit allows you to tailor applications to meet the needs of your users, handle your specific data, and address the critical questions at hand. It is compatible with all browsers, devices, servers, and databases, and is supported by comprehensive tutorials, demonstrations, and detailed API documentation. With our dedicated developer support, you will be able to reveal network insights efficiently. KeyLines simplifies the process of creating high-performance JavaScript graph visualization tools that operate seamlessly across various platforms. By leveraging HTML5 and WebGL for graphics rendering alongside meticulously designed code, users will enjoy rapid and meaningful visual representation of their data. Additionally, these tools empower users to make informed decisions based on the insights they uncover.

Create innovative React graph visualization tools that transform interconnected data into valuable insights. With ReGraph’s user-friendly data-driven API, you can seamlessly incorporate graph visualizations into your React applications in no time. Deliver tailored, high-performance graph visualizations to your users, no matter where they are located. For React developers, ReGraph provides a straightforward and organized coding experience, featuring familiar logic, straightforward state management, and thorough documentation for its props. You have the freedom to determine where your data is hosted and how your components will look and function. This solution is compatible across all browsers and devices, effortlessly integrating with any server or database. It offers a completely adaptable approach to constructing a custom React graph visualization application. ReGraph simplifies the process of developing robust React graph visualization applications, with every aspect meticulously optimized for peak performance, including its layout algorithms and an advanced graphics rendering engine. This flexibility empowers developers to create unique visual experiences tailored to their specific needs.

Autobox is the most user-friendly solution for forecasting available today. Tailored for both beginners and seasoned professionals, it allows users to input their data and generate forecasts with expert-level accuracy. Regardless of your current forecasting technique, Autobox enhances your precision in predictions significantly. This innovative tool has been recognized as the “best-dedicated forecasting program” in the esteemed Principles of Forecasting textbook and has transitioned into an online platform. The unique methodology employed by AFS does not confine data to a rigid model or a small selection of models, enabling Autobox to optimally integrate historical data and causal factors while addressing level shifts, local time trends, pulses, and seasonal variations as needed. The Autobox engine is adept at uncovering new causal variables by analyzing patterns within historical forecast errors and outliers, often revealing causal factors that users may have been unaware of, such as promotions, holidays, and day-of-the-week influences. This capability allows users to harness a broader range of insights, ultimately leading to more refined and actionable forecasts.

Astra DB from DataStax is a real-time vector database as a service for developers that need to get accurate Generative AI applications into production, fast. Astra DB gives you a set of elegant APIs supporting multiple languages and standards, powerful data pipelines and complete ecosystem integrations. Astra DB enables you to quickly build Gen AI applications on your real-time data for more accurate AI that you can deploy in production. Built on Apache Cassandra, Astra DB is the only vector database that can make vector updates immediately available to applications and scale to the largest real-time data and streaming workloads, securely on any cloud. Astra DB offers unprecedented serverless, pay as you go pricing and the flexibility of multi-cloud and open-source. You can store up to 80GB and/or perform 20 million operations per month. Securely connect to VPC peering and private links. Manage your encryption keys with your own key management. SAML SSO secure account accessibility. You can deploy on Amazon, Google Cloud, or Microsoft Azure while still compatible with open-source Apache Cassandra.

Engaging applications captivate users while motivating developers to innovate. To meet the growing demands of the digital landscape, consider utilizing the DataStax Astra Streaming service platform. This cloud-native platform for messaging and event streaming is built on the robust foundation of Apache Pulsar. With Astra Streaming, developers can create streaming applications that leverage a multi-cloud, elastically scalable architecture. Powered by the advanced capabilities of Apache Pulsar, this platform offers a comprehensive solution that encompasses streaming, queuing, pub/sub, and stream processing. Astra Streaming serves as an ideal partner for Astra DB, enabling current users to construct real-time data pipelines seamlessly connected to their Astra DB instances. Additionally, the platform's flexibility allows for deployment across major public cloud providers, including AWS, GCP, and Azure, thereby preventing vendor lock-in. Ultimately, Astra Streaming empowers developers to harness the full potential of their data in real-time environments.