Alternatives to Toad Data Point

BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises. Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.

Improvado, an ETL solution, facilitates data pipeline automation for marketing departments without any technical skills. This platform supports marketers in making data-driven, informed decisions. It provides a comprehensive solution for integrating marketing data across an organization. Improvado extracts data form a marketing data source, normalizes it and seamlessly loads it into a marketing dashboard. It currently has over 200 pre-built connectors. On request, the Improvado team will create new connectors for clients. Improvado allows marketers to consolidate all their marketing data in one place, gain better insight into their performance across channels, analyze attribution models, and obtain accurate ROMI data. Companies such as Asus, BayCare and Monster Energy use Improvado to mark their markes.

IBM® SPSS® Statistics software is used by a variety of customers to solve industry-specific business issues to drive quality decision-making. The IBM® SPSS® software platform offers advanced statistical analysis, a vast library of machine learning algorithms, text analysis, open-source extensibility, integration with big data and seamless deployment into applications. Its ease of use, flexibility and scalability make SPSS accessible to users of all skill levels. What’s more, it’s suitable for projects of all sizes and levels of complexity, and can help you find new opportunities, improve efficiency and minimize risk.

With more than three decades of expertise in data discovery and transformation, Altair Monarch stands out as an industry pioneer, providing the quickest and most user-friendly method for extracting data from a variety of sources. Users can easily create workflows without any coding knowledge, allowing for collaboration in transforming challenging data formats like PDFs, spreadsheets, text files, as well as data from big data sources and other structured formats into organized rows and columns. Regardless of whether the data is stored locally or in the cloud, Altair Monarch streamlines preparation tasks, leading to faster outcomes and delivering reliable data that supports informed business decision-making. This robust solution empowers organizations to harness their data effectively, ultimately driving growth and innovation. For more information about Altair Monarch or to access a free version of its enterprise software, please click the links provided below.

The most accurate, complete, and timely data provides the best insight. Minitab Connect empowers data users across the enterprise with self service tools to transform diverse data into a network of data pipelines that feed analytics initiatives, foster collaboration and foster organizational-wide collaboration. Users can seamlessly combine and explore data from various sources, including databases, on-premise and cloud apps, unstructured data and spreadsheets. Automated workflows make data integration faster and provide powerful data preparation tools that allow for transformative insights. Data integration tools that are intuitive and flexible allow users to connect and blend data from multiple sources such as data warehouses, IoT devices and cloud storage.

In today’s constantly connected economy, the volume of data generated is skyrocketing. It’s crucial to adopt a data-driven approach that enables rapid responses and innovations to stay ahead of your rivals. Imagine if you could streamline the processes of data preparation and provisioning. Consider the benefits of conducting database analysis with ease and sharing valuable data insights among analysts across various teams. What if achieving all of this could lead to time savings of up to 40%? When paired with Toad® Data Point, Toad Intelligence Central serves as a budget-friendly, server-based solution that empowers your organization. It enhances collaboration among Toad users by providing secure and governed access to SQL scripts, project artifacts, provisioned data, and automation workflows. Furthermore, it allows for seamless abstraction of both structured and unstructured data sources through advanced connectivity, enabling the creation of refreshable datasets accessible to any Toad user. Ultimately, this integration not only optimizes efficiency but also fosters a culture of data-driven decision-making within your organization.

JMP, data analysis software Mac and Windows, combines powerful statistics with interactive visualization. It is simple to import and process data. Drag-and-drop interface, dynamically linked graphics, libraries of advanced analytics functionality, scripting language, and ways to share findings with others allow users to dig deeper into their data with greater ease. JMP was originally developed in 1980 to capture the new value of GUI for personal computers. JMP continues to add cutting-edge statistical methods to the software's functionality with every release. John Sall, the organization's founder, is still Chief Architect.

Quickly prepare data to provide trusted insights across the organization. Business analysts and data scientists spend too much time cleaning out data rather than analyzing it. Talend Data Preparation is a self-service, browser-based tool that allows you to quickly identify errors and create rules that can be reused and shared across large data sets. With our intuitive user interface and self-service data preparation/curation functionality, anyone can perform data profiling, cleansing, enriching and enrichment in real time. Users can share prepared datasets and curated data, and embed data preparations in batch, bulk, or live data integration scenarios. Talend allows you to transform ad-hoc analysis and data enrichment jobs into fully managed, reusable process. You can use any data source, including Teradata and AWS, Salesforce and Marketo, to operationalize data preparation. Always using the most recent datasets. Talend Data Preparation gives you control over data governance.

Kylo serves as an open-source platform designed for effective management of enterprise-level data lakes, facilitating self-service data ingestion and preparation while also incorporating robust metadata management, governance, security, and best practices derived from Think Big's extensive experience with over 150 big data implementation projects. It allows users to perform self-service data ingestion complemented by features for data cleansing, validation, and automatic profiling. Users can manipulate data effortlessly using visual SQL and an interactive transformation interface that is easy to navigate. The platform enables users to search and explore both data and metadata, examine data lineage, and access profiling statistics. Additionally, it provides tools to monitor the health of data feeds and services within the data lake, allowing users to track service level agreements (SLAs) and address performance issues effectively. Users can also create batch or streaming pipeline templates using Apache NiFi and register them with Kylo, thereby empowering self-service capabilities. Despite organizations investing substantial engineering resources to transfer data into Hadoop, they often face challenges in maintaining governance and ensuring data quality, but Kylo significantly eases the data ingestion process by allowing data owners to take control through its intuitive guided user interface. This innovative approach not only enhances operational efficiency but also fosters a culture of data ownership within organizations.

DataPreparator is a complimentary software application aimed at facilitating various aspects of data preparation, also known as data preprocessing, within the realms of data analysis and mining. This tool provides numerous functionalities to help you explore and ready your data before engaging in analysis or mining activities. It encompasses a range of features including data cleaning, discretization, numerical adjustments, scaling, attribute selection, handling missing values, addressing outliers, conducting statistical analyses, visualizations, balancing, sampling, and selecting specific rows, among other essential tasks. The software allows users to access data from various sources such as text files, relational databases, and Excel spreadsheets. It is capable of managing substantial data volumes effectively, as datasets are not retained in computer memory, except for Excel files and the result sets from certain databases that lack data streaming support. As a standalone tool, it operates independently of other applications, boasting a user-friendly graphical interface. Additionally, it enables operator chaining to form sequences of preprocessing transformations and allows for the creation of a model tree specifically for test or execution data, thereby enhancing the overall data preparation process. Ultimately, DataPreparator serves as a versatile and efficient resource for those engaged in data-related tasks.

No per-connection charges for setting up all the automated connections that you need. No per-connection fees for all the automated connections that you need. No technical expertise is required to set up and scale your cloud data warehouse or processing operations. Conversionomics allows you to make mistakes and ask hard questions about your data. You have the power to do whatever you want with your data. Conversionomics creates complex SQL to combine source data with lookups and table relationships. You can use preset joins and common SQL, or create your own SQL to customize your query. Conversionomics is a data aggregation tool with a simple interface that makes it quick and easy to create data API sources. You can create interactive dashboards and reports from these sources using our templates and your favorite data visualization tools.

Zoho DataPrep is an advanced self-service data preparation software that helps organizations prepare data by allowing import from a variety of sources, automatically identifying errors, discovering data patterns, transforming and enriching data and scheduling export all without the need for coding.

Analysts can leverage drag-and-drop tools alongside generative AI to prepare and blend data up to 100 times faster compared to traditional methods. A self-service data analytics platform empowers every analyst by eliminating costly bottlenecks in the analytics process. Alteryx Designer stands out as a self-service data analytics solution that equips analysts to effectively prepare, blend, and analyze data through user-friendly, drag-and-drop interfaces. The platform boasts compatibility with over 300 automation tools and integrates seamlessly with more than 80 data sources. By prioritizing low-code and no-code features, Alteryx Designer allows users to construct analytic workflows effortlessly, expedite analytical tasks using generative AI, and derive insights without requiring extensive programming knowledge. Additionally, it facilitates the export of results to more than 70 different tools, showcasing its exceptional versatility. Overall, this design enhances operational efficiency, enabling organizations to accelerate their data preparation and analytical processes significantly.

Self-service analytics tools were designed to empower end-users by enhancing their agility and fostering a data-driven culture. Unfortunately, this boost in agility often resulted in fragmented and isolated workflows due to a lack of data governance, leading to chaotic data management practices. Knowledge Hub offers a solution that effectively tackles these challenges, benefiting business users while simultaneously streamlining and fortifying IT governance. Featuring an easy-to-use browser-based interface, it automates the tasks involved in data transformation, making it the only collaborative data preparation tool available in today's market. This enables business teams to collaborate effortlessly with data engineers and scientists, providing a tailored experience for creating, validating, and sharing datasets and analytical models that are both governed and reliable. With no coding necessary, a wider audience can contribute to collaborative efforts, ultimately leading to better-informed decision-making. Governance, data lineage, and collaboration are seamlessly managed within a cloud-compatible solution specifically designed to foster innovation. Additionally, the platform's extensibility and low- to no-code capabilities empower individuals from various departments to efficiently transform data, encouraging a culture of shared insights and collaboration throughout the organization.

The fundamental technology that powers contemporary solutions for data integration and management is designed to swiftly link various structured and unstructured data sources. It allows for the comprehensive cataloging of your entire data environment, ensuring that data remains within its original sources and is retrieved as needed, eliminating the requirement for duplicate copies. Users can construct data models tailored to their needs, even when drawing from multiple data sources, while also concealing the intricacies of back-end systems from end users. The virtual model can be securely accessed and utilized through standard SQL alongside other formats such as REST, SOAP, and OData, promoting easy access to diverse data types. It features complete data integration and modeling capabilities, along with an Active Data Catalog that enables self-service for data and metadata exploration and preparation. Furthermore, it incorporates robust data security and governance measures, ensures rapid and intelligent execution of data queries, and provides real-time data delivery in various formats. The system also supports the establishment of data marketplaces and effectively decouples business applications from data systems, paving the way for more informed, data-driven decision-making strategies. This innovative approach enhances the overall agility and responsiveness of organizations in managing their data assets.

Numerous individuals rely on Excel, VBA/Python scripts, or SQL queries for preparing data, often due to a lack of awareness of superior options available. EasyMorph stands out as a dedicated tool that offers over 150 built-in actions designed for quick and visual data transformation and automation, all without the need for coding skills. By utilizing EasyMorph, you can move beyond complex scripts and unwieldy spreadsheets, significantly enhancing your productivity. This application allows you to seamlessly retrieve data from a variety of sources such as databases, spreadsheets, emails and their attachments, text files, remote folders, corporate applications like SharePoint, and web APIs, all without needing programming expertise. You can employ visual tools and queries to filter and extract precisely the information you require, eliminating the need to consult IT for assistance. Moreover, it enables you to automate routine tasks associated with files, spreadsheets, websites, and emails with no coding required, transforming tedious and repetitive actions into a simple button click. With EasyMorph, not only is the data preparation process simplified, but users can also focus on more strategic tasks instead of getting bogged down in the minutiae of data handling.

Power Query provides a user-friendly solution for connecting, extracting, transforming, and loading data from a variety of sources. Acting as a robust engine for data preparation and transformation, Power Query features a graphical interface that simplifies the data retrieval process and includes a Power Query Editor for implementing necessary changes. The versatility of the engine allows it to be integrated across numerous products and services, meaning the storage location of the data is determined by the specific application of Power Query. This tool enables users to efficiently carry out the extract, transform, and load (ETL) processes for their data needs. With Microsoft’s Data Connectivity and Data Preparation technology, users can easily access and manipulate data from hundreds of sources in a straightforward, no-code environment. Power Query is equipped with support for a multitude of data sources through built-in connectors, generic interfaces like REST APIs, ODBC, OLE, DB, and OData, and even offers a Power Query SDK for creating custom connectors tailored to individual requirements. This flexibility makes Power Query an indispensable asset for data professionals seeking to streamline their workflows.

Dataiku serves as a sophisticated platform for data science and machine learning, aimed at facilitating teams in the construction, deployment, and management of AI and analytics projects on a large scale. It enables a diverse range of users, including data scientists and business analysts, to work together in developing data pipelines, crafting machine learning models, and preparing data through various visual and coding interfaces. Supporting the complete AI lifecycle, Dataiku provides essential tools for data preparation, model training, deployment, and ongoing monitoring of projects. Additionally, the platform incorporates integrations that enhance its capabilities, such as generative AI, thereby allowing organizations to innovate and implement AI solutions across various sectors. This adaptability positions Dataiku as a valuable asset for teams looking to harness the power of AI effectively.

Coheris Spad, developed by ChapsVision, serves as a self-service data analysis platform tailored for Data Scientists across diverse sectors and industries. This tool is widely recognized and incorporated into numerous prestigious French and international educational institutions, solidifying its esteemed status among Data Scientists. Coheris Spad offers an extensive methodological framework that encompasses a wide array of data analysis techniques. Users benefit from a friendly and intuitive interface that equips them with the necessary capabilities to explore, prepare, and analyze their data effectively. The platform supports connections to multiple data sources for efficient data preparation. Additionally, it boasts a comprehensive library of data processing functions, including filtering, stacking, aggregation, transposition, joining, handling of missing values, identification of unusual distributions, statistical or supervised recoding, and formatting options, empowering users to perform thorough and insightful analyses. Furthermore, the flexibility and versatility of Coheris Spad make it an invaluable asset for both novice and experienced data practitioners.

Paxata is an innovative, user-friendly platform that allows business analysts to quickly ingest, analyze, and transform various raw datasets into useful information independently, significantly speeding up the process of generating actionable business insights. Besides supporting business analysts and subject matter experts, Paxata offers an extensive suite of automation tools and data preparation features that can be integrated into other applications to streamline data preparation as a service. The Paxata Adaptive Information Platform (AIP) brings together data integration, quality assurance, semantic enhancement, collaboration, and robust data governance, all while maintaining transparent data lineage through self-documentation. Utilizing a highly flexible multi-tenant cloud architecture, Paxata AIP stands out as the only contemporary information platform that operates as a multi-cloud hybrid information fabric, ensuring versatility and scalability in data handling. This unique approach not only enhances efficiency but also fosters collaboration across different teams within an organization.

Trifacta offers an efficient solution for preparing data and constructing data pipelines in the cloud. By leveraging visual and intelligent assistance, it enables users to expedite data preparation, leading to quicker insights. Data analytics projects can falter due to poor data quality; therefore, Trifacta equips you with the tools to comprehend and refine your data swiftly and accurately. It empowers users to harness the full potential of their data without the need for coding expertise. Traditional manual data preparation methods can be tedious and lack scalability, but with Trifacta, you can create, implement, and maintain self-service data pipelines in mere minutes instead of months, revolutionizing your data workflow. This ensures that your analytics projects are not only successful but also sustainable over time.

MassFeeds serves as a specialized tool for data preparation that automates and expedites the organization of data originating from diverse sources and formats. This innovative solution is crafted to enhance and streamline the data preparation workflow by generating automated data pipelines specifically tailored for marketing mix models. As the volume of data generation and collection continues to surge, organizations can no longer rely on labor-intensive manual processes for data preparation to keep pace. MassFeeds empowers clients to efficiently manage data from various origins and formats through a smooth, automated, and easily adjustable approach. By utilizing MassFeeds’ suite of processing pipelines, data is transformed into a standardized format, ensuring effortless integration into modeling systems. This tool helps eliminate the risks associated with manual data preparation, which can often lead to human errors. Moreover, it broadens access to data processing for a larger range of users and boasts the potential to reduce processing times by over 40% by automating repetitive tasks, ultimately leading to more efficient operations across the board. With MassFeeds, organizations can experience a significant boost in their data management capabilities.

Amazon SageMaker Data Wrangler significantly shortens the data aggregation and preparation timeline for machine learning tasks from several weeks to just minutes. This tool streamlines data preparation and feature engineering, allowing you to execute every phase of the data preparation process—such as data selection, cleansing, exploration, visualization, and large-scale processing—through a unified visual interface. You can effortlessly select data from diverse sources using SQL, enabling rapid imports. Following this, the Data Quality and Insights report serves to automatically assess data integrity and identify issues like duplicate entries and target leakage. With over 300 pre-built data transformations available, SageMaker Data Wrangler allows for quick data modification without the need for coding. After finalizing your data preparation, you can scale the workflow to encompass your complete datasets, facilitating model training, tuning, and deployment in a seamless manner. This comprehensive approach not only enhances efficiency but also empowers users to focus on deriving insights from their data rather than getting bogged down in the preparation phase.

An agile platform for end-to-end DataOps that not only enhances but also protects your data assets is available through Arena, the leading augmented data management solution. With our dynamic data catalog, users can enrich and access data independently, facilitating efficient management of intricate data landscapes. Tailored workflows enhance the precision and dependability of every dataset, while machine learning identifies and aligns master data assets to facilitate superior decision-making. Comprehensive lineage tracking, accompanied by intricate visualizations and advanced security measures like masking and tokenization, ensures utmost protection. Our platform simplifies data management by cataloging data from any location, with flexible connections that allow analytics to integrate seamlessly with your chosen tools. Additionally, our software effectively addresses the challenges of data sprawl, driving success in business and analytics while offering essential controls and adaptability in today’s diverse, multi-cloud data environments. As organizations increasingly rely on data, Arena stands out as a vital partner in navigating this complexity.

Embrace a groundbreaking age of analytics through the Alteryx AI Platform. Equip your organization with streamlined data preparation, analytics powered by artificial intelligence, and accessible machine learning, all while ensuring governance and security are built in. This marks the dawn of a new era for data-driven decision-making accessible to every user and team at all levels. Enhance your teams' capabilities with a straightforward, user-friendly interface that enables everyone to develop analytical solutions that boost productivity, efficiency, and profitability. Foster a robust analytics culture by utilizing a comprehensive cloud analytics platform that allows you to convert data into meaningful insights via self-service data preparation, machine learning, and AI-generated findings. Minimize risks and safeguard your data with cutting-edge security protocols and certifications. Additionally, seamlessly connect to your data and applications through open API standards, facilitating a more integrated and efficient analytical environment. By adopting these innovations, your organization can thrive in an increasingly data-centric world.

Datuum is an AI-powered data integration tool that offers a unique solution for organizations looking to streamline their data integration process. With our pre-trained AI engine, Datuum simplifies customer data onboarding by allowing for automated integration from various sources without coding. This reduces data preparation time and helps establish resilient connectors, ultimately freeing up time for organizations to focus on generating insights and improving the customer experience. At Datuum, we have over 40 years of experience in data management and operations, and we've incorporated our expertise into the core of our product. Our platform is designed to address the critical challenges faced by data engineers and managers while being accessible and user-friendly for non-technical specialists. By reducing up to 80% of the time typically spent on data-related tasks, Datuum can help organizations optimize their data management processes and achieve more efficient outcomes.

TROCCO is an all-in-one modern data platform designed to help users seamlessly integrate, transform, orchestrate, and manage data through a unified interface. It boasts an extensive array of connectors that encompass advertising platforms such as Google Ads and Facebook Ads, cloud services like AWS Cost Explorer and Google Analytics 4, as well as various databases including MySQL and PostgreSQL, and data warehouses such as Amazon Redshift and Google BigQuery. One of its standout features is Managed ETL, which simplifies the data import process by allowing bulk ingestion of data sources and offers centralized management for ETL configurations, thereby removing the necessity for individual setup. Furthermore, TROCCO includes a data catalog that automatically collects metadata from data analysis infrastructure, creating a detailed catalog that enhances data accessibility and usage. Users have the ability to design workflows that enable them to organize a sequence of tasks, establishing an efficient order and combination to optimize data processing. This capability allows for increased productivity and ensures that users can better capitalize on their data resources.

Effortlessly load your data into or extract it from Hadoop and data lakes, ensuring it is primed for generating reports, visualizations, or conducting advanced analytics—all within the data lakes environment. This streamlined approach allows you to manage, transform, and access data stored in Hadoop or data lakes through a user-friendly web interface, minimizing the need for extensive training. Designed specifically for big data management on Hadoop and data lakes, this solution is not simply a rehash of existing IT tools. It allows for the grouping of multiple directives to execute either concurrently or sequentially, enhancing workflow efficiency. Additionally, you can schedule and automate these directives via the public API provided. The platform also promotes collaboration and security by enabling the sharing of directives. Furthermore, these directives can be invoked from SAS Data Integration Studio, bridging the gap between technical and non-technical users. It comes equipped with built-in directives for various tasks, including casing, gender and pattern analysis, field extraction, match-merge, and cluster-survive operations. For improved performance, profiling processes are executed in parallel on the Hadoop cluster, allowing for the seamless handling of large datasets. This comprehensive solution transforms the way you interact with data, making it more accessible and manageable than ever.

For more four decades, IRI CoSort has defined the state-of-the-art in big data sorting and transformation technology. From advanced algorithms to automatic memory management, and from multi-core exploitation to I/O optimization, there is no more proven performer for production data processing than CoSort. CoSort was the first commercial sort package developed for open systems: CP/M in 1980, MS-DOS in 1982, Unix in 1985, and Windows in 1995. Repeatedly reported to be the fastest commercial-grade sort product for Unix. CoSort was also judged by PC Week to be the "top performing" sort on Windows. CoSort was released for CP/M in 1978, DOS in 1980, Unix in the mid-eighties, and Windows in the early nineties, and received a readership award from DM Review magazine in 2000. CoSort was first designed as a file sorting utility, and added interfaces to replace or convert sort program parameters used in IBM DataStage, Informatica, MF COBOL, JCL, NATURAL, SAS, and SyncSort. In 1992, CoSort added related manipulation functions through a control language interface based on VMS sort utility syntax, which evolved through the years to handle structured data integration and staging for flat files and RDBs, and multiple spinoff products.

Introducing a no-code platform designed for data cleaning, preparation, and machine learning tailored specifically for business applications, with options for on-premise installation to ensure data privacy. You can take advantage of Sweephy's complimentary modules right away, which offer no-code tools powered by machine learning. Simply provide the data and the keywords you wish to analyze, and our model will generate a comprehensive report based on those keywords. Beyond just a basic word check, our advanced model conducts semantic and grammatical classification to enhance accuracy. We can also assist in identifying duplicate or similar records within your database, facilitating the creation of a consolidated user database from various data sources using the Sweephy Dedupu API. Additionally, with our API, you can effortlessly develop object detection models by fine-tuning existing pre-trained models; just share your use cases and we will craft a suitable model tailored to your needs. This could include tasks like classifying documents, PDFs, receipts, or invoices. Simply upload your image dataset, and our model will efficiently eliminate any noise from the images or develop a specialized model to meet your specific business requirements. Our commitment to customer satisfaction ensures you receive a solution perfectly aligned with your goals.

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.

Over four decades and numerous clients, we have meticulously crafted our analytics platform, continually refining our methods to cater to the evolving needs of modern enterprises. In today's landscape, this translates into advanced visualization, immediate insights, and the capacity to make data universally accessible. Our singular focus is to enhance your business outcomes by facilitating informed decision-making processes. It's essential that a well-structured data strategy is supported by easily accessible data. The manner in which you interpret your data—its trends and patterns—significantly influences its practical utility. By implementing real-time, tailored, and self-service dashboards, you can empower your organization to make strategic decisions with confidence, rather than relying on instinct or grappling with uncertainty. With outstanding visualization and reporting capabilities, your entire organization can unite around shared information, fostering growth and collaboration. Ultimately, this transformation is not merely about data; it's about enabling a culture of data-driven decision-making that propels your business forward.

Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.

Effortlessly link your data to the engine by either uploading a file or establishing a connection to a database. Once connected, you can begin to explore your data through various visualizations, or you can prepare it for machine learning modeling using data wrangling techniques and reusable recipes. Maximize the potential of your data by constructing machine learning models with regression, classification, or clustering algorithms—all without requiring any coding skills. Discover valuable insights into your dataset through tools that highlight feature importance, explain predictions, and allow for scenario analysis. Additionally, you can make forecasts and easily integrate them into your current systems using our pre-configured connectors, enabling you to take immediate action based on your findings. This streamlined process empowers you to unlock the full value of your data and drive informed decision-making.

Trifacta's Cloud Dataprep is an advanced data service designed for the visual exploration, cleansing, and preparation of both structured and unstructured datasets, facilitating analysis, reporting, and machine learning tasks. Its serverless architecture allows it to operate at any scale, eliminating the need for users to manage or deploy infrastructure. With each interaction in the user interface, the system intelligently suggests and forecasts your next ideal data transformation, removing the necessity for manual coding. As a partner service of Trifacta, Cloud Dataprep utilizes their renowned data preparation technology to enhance functionality. Google collaborates closely with Trifacta to ensure a fluid user experience, which bypasses the requirement for initial software installations, separate licensing fees, or continuous operational burdens. Fully managed and capable of scaling on demand, Cloud Dataprep effectively adapts to your evolving data preparation requirements, allowing you to concentrate on your analytical pursuits. This innovative service ultimately empowers users to streamline their workflows and maximize productivity.

The data refinery tool, which can be accessed through IBM Watson® Studio and Watson™ Knowledge Catalog, significantly reduces the time spent on data preparation by swiftly converting extensive volumes of raw data into high-quality, usable information suitable for analytics. Users can interactively discover, clean, and transform their data using more than 100 pre-built operations without needing any coding expertise. Gain insights into the quality and distribution of your data with a variety of integrated charts, graphs, and statistical tools. The tool automatically identifies data types and business classifications, ensuring accuracy and relevance. It also allows easy access to and exploration of data from diverse sources, whether on-premises or cloud-based. Data governance policies set by professionals are automatically enforced within the tool, providing an added layer of compliance. Users can schedule data flow executions for consistent results and easily monitor those results while receiving timely notifications. Furthermore, the solution enables seamless scaling through Apache Spark, allowing transformation recipes to be applied to complete datasets without the burden of managing Apache Spark clusters. This feature enhances efficiency and effectiveness in data processing, making it a valuable asset for organizations looking to optimize their data analytics capabilities.

Oracle Analytics is a comprehensive platform designed for all analytics user roles, integrating AI and machine learning across the board to boost productivity and enable smarter business decisions. Whether you opt for Oracle Analytics Cloud, our cloud-native service, or Oracle Analytics Server, our on-premises solution, you can ensure robust security and governance without compromise.

BDB is an advanced platform for data analytics and business intelligence that excels in extracting valuable insights from your data. It can be implemented both in cloud environments and on-premises. With a unique microservices architecture, it incorporates components for Data Preparation, Predictive Analytics, Pipelines, and Dashboard design, enabling tailored solutions and scalable analytics across various sectors. Thanks to its robust NLP-driven search functionality, users can harness the potential of data seamlessly across desktops, tablets, and mobile devices. BDB offers numerous integrated data connectors, allowing it to interface with a wide array of popular data sources, applications, third-party APIs, IoT devices, and social media platforms in real-time. It facilitates connections to relational databases, big data systems, FTP/SFTP servers, flat files, and web services, effectively managing structured, semi-structured, and unstructured data. Embark on your path to cutting-edge analytics today, and discover the transformative power of BDB for your organization.

Tableau Prep revolutionizes traditional data preparation within organizations by offering an intuitive visual interface for data merging, shaping, and cleansing, enabling analysts and business users to initiate their analysis more swiftly. It consists of two key products: Tableau Prep Builder, designed for creating data flows, and Tableau Prep Conductor, which facilitates the scheduling, monitoring, and management of those flows throughout the organization. Users can leverage three different views to examine row-level details, column profiles, and the overall data preparation workflow, allowing them to choose the most appropriate view based on their specific tasks. Editing a value is as simple as selecting it and making changes directly, while modifications to join types yield immediate results, ensuring real-time feedback even with extensive datasets. Every action taken allows for instant visualization of data changes, regardless of the volume, and Tableau Prep Builder empowers users to reorder steps and experiment freely without risk. This flexibility fosters a more dynamic data preparation process, encouraging innovation and efficiency in data handling.

Based in Indonesia, our company specializes in managing data efficiently. We offer both a product and consulting services tailored to meet diverse needs. The name Delman is a fusion of "Data Excavation Learning and Management," symbolizing our commitment to delivering data science solutions centered around data preparation. Our goal is to facilitate digital transformation by seamlessly integrating and managing countless data sources with greater efficiency. We have successfully served a variety of sectors, including enterprises, conglomerates, and government entities in Indonesia. Our team possesses a robust blend of technical and operational expertise, establishing a unique presence within the country's deep tech ecosystem. We are confident that by adopting international best practices, we can create the most advanced and effective tools in the market. At Delman, we believe that the synergy of diverse talents and experiences is key to providing exceptional solutions that drive success. By constantly innovating and adapting, we aim to stay ahead of the curve in the rapidly evolving data landscape.

Verodat, a SaaS-platform, gathers, prepares and enriches your business data, then connects it to AI Analytics tools. For results you can trust. Verodat automates data cleansing & consolidates data into a clean, trustworthy data layer to feed downstream reporting. Manages data requests for suppliers. Monitors data workflows to identify bottlenecks and resolve issues. The audit trail is generated to prove quality assurance for each data row. Validation & governance can be customized to your organization. Data preparation time is reduced by 60% allowing analysts to focus more on insights. The central KPI Dashboard provides key metrics about your data pipeline. This allows you to identify bottlenecks and resolve issues, as well as improve performance. The flexible rules engine allows you to create validation and testing that suits your organization's requirements. It's easy to integrate your existing tools with the out-of-the box connections to Snowflake and Azure.

The HyperSense platform is a cloud-native, SaaS-based augmented analytics solution designed to assist enterprises in making quicker and more informed decisions by utilizing Artificial Intelligence (AI) throughout the data value chain. It seamlessly integrates data from various sources, generates insights by developing, interpreting, and refining AI models, and disseminates these insights organization-wide. Acting as a comprehensive solution, HyperSense accelerates decision-making in telecom enterprises through its self-service AI capabilities. With its no-code interface, the platform is user-friendly and quick to set up, enabling business users, domain specialists, and data scientists to collaboratively create and manage AI models across the entire organization. This innovative approach not only enhances operational efficiency but also fosters a data-driven culture in the workplace.

Stata delivers everything you need for reproducible data analysis—powerful statistics, visualization, data manipulation, and automated reporting—all in one intuitive platform. Stata is quick and accurate. The extensive graphical interface makes it easy to use, but is also fully programable. Stata's menus, dialogs and buttons give you the best of both worlds. All Stata's data management, statistical, and graphical features are easy to access by dragging and dropping or point-and-click. To quickly execute commands, you can use Stata's intuitive command syntax. You can log all actions and results, regardless of whether you use the menus or dialogs. This will ensure reproducibility and integrity in your analysis. Stata also offers complete command-line programming and programming capabilities, including a full matrix language. All the commands that Stata ships with are available to you, whether you want to create new Stata commands or script your analysis.

Utilize Weights & Biases (WandB) for experiment tracking, hyperparameter tuning, and versioning of both models and datasets. With just five lines of code, you can efficiently monitor, compare, and visualize your machine learning experiments. Simply enhance your script with a few additional lines, and each time you create a new model version, a fresh experiment will appear in real-time on your dashboard. Leverage our highly scalable hyperparameter optimization tool to enhance your models' performance. Sweeps are designed to be quick, easy to set up, and seamlessly integrate into your current infrastructure for model execution. Capture every aspect of your comprehensive machine learning pipeline, encompassing data preparation, versioning, training, and evaluation, making it incredibly straightforward to share updates on your projects. Implementing experiment logging is a breeze; just add a few lines to your existing script and begin recording your results. Our streamlined integration is compatible with any Python codebase, ensuring a smooth experience for developers. Additionally, W&B Weave empowers developers to confidently create and refine their AI applications through enhanced support and resources.

Are you looking for a reliable way to regularly update or synchronize your DBF files? DBF Sync offers a complete solution tailored to meet your needs! This tool is not only cost-effective but also essential and user-friendly for IT professionals, DBF system administrators, and various database users who require routine data maintenance. A common application of DBF Sync is the ability to refresh fields in a primary file using data from an update file, with both sets of fields being easily selectable within the tool. Additionally, DBF Sync enables users to create projects that store configuration settings and file specifics for convenient future access. Beyond its intuitive wizard interface, the software also features a command line option and can be set up to run automatically through application schedulers like the Windows Scheduled Tasks utility. This functionality allows for seamless integration of DBF Sync into your existing data management processes. Moreover, to protect your data, DBF Sync includes a simulation mode that can be utilized for testing purposes before making any changes. This ensures that users can confidently manage their database updates without any risk to their data integrity.

Telegraf is an open-source server agent that helps you collect metrics from your sensors, stacks, and systems. Telegraf is a plugin-driven agent that collects and sends metrics and events from systems, databases, and IoT sensors. Telegraf is written in Go. It compiles to a single binary and has no external dependencies. It also requires very little memory. Telegraf can gather metrics from a wide variety of inputs and then write them into a wide range of outputs. It can be easily extended by being plugin-driven for both the collection and output data. It is written in Go and can be run on any system without external dependencies. It is easy to collect metrics from your endpoints with the 300+ plugins that have been created by data experts in the community.

Unlock the potential to redefine business intelligence. With ElegantJ BI tools and solutions, envision the vast opportunities that come from empowering business users to harness their own analytics. Picture a scenario where users can perform in-depth analyses and move away from the limitations of traditional 'static dashboards.' Equip your team to evolve into citizen data scientists using Smarten, our advanced data discovery platform powered by ElegantJ BI. Our self-service mobile business intelligence suite caters to enterprises of all sizes, various business functions, and diverse user needs. It offers a comprehensive array of tools and advanced features in a user-friendly interface designed to facilitate the transformation of business users into adept citizen data scientists. We not only advocate for mobile business intelligence, we ensure its practical implementation! You have the freedom to choose the device, screen size, or environment from which you can access essential business intelligence data. Ultimately, our goal is to enhance decision-making across your organization by making data accessible anywhere, anytime.

Elevate your AI and data initiatives by harnessing the power of premium data. At Synthesized, we fully realize the potential of data by utilizing advanced AI to automate every phase of data provisioning and preparation. Our innovative platform ensures adherence to privacy and compliance standards, thanks to the synthesized nature of the data it generates. We offer software solutions for crafting precise synthetic data, enabling organizations to create superior models at scale. By partnering with Synthesized, businesses can effectively navigate the challenges of data sharing. Notably, 40% of companies investing in AI struggle to demonstrate tangible business benefits. Our user-friendly platform empowers data scientists, product managers, and marketing teams to concentrate on extracting vital insights, keeping you ahead in a competitive landscape. Additionally, the testing of data-driven applications can present challenges without representative datasets, which often results in complications once services are launched. By utilizing our services, organizations can significantly mitigate these risks and enhance their operational efficiency.

Transforming a week's labor of manual data preparation into mere minutes, our innovative Data Preparer software streamlines the path to insights through intelligent data handling. This fresh approach to data preparation allows users to specify their requirements, letting the software automatically determine the best way to fulfill them. With Data Preparer, labor-intensive programming is no longer necessary, as it efficiently manages data preparation tasks without the need for intricate coding. Users simply outline their needs, supplying data sources, a desired structure, quality benchmarks, and sample data. The clarity provided by the target structure and quality priorities ensures precise requirements, while the example data aids Data Preparer in efficiently cleaning and integrating the datasets. Once the parameters are set, Data Preparer takes over, analyzing relationships between the various data sources and the intended target, effectively populating the target with the necessary information. Moreover, it assesses multiple methods for combining the sources and adapts the data format accordingly, making the entire process seamless and user-friendly. In this way, Data Preparer not only simplifies the data preparation process but also enhances the overall quality of the analysis.

Bipp's cloud BI platform, built on the innovative bippLang data modeling language, was crafted specifically for SQL and data analysts from its inception. It enhances productivity for teams, equipping businesses to make quicker and more informed decisions. The bippLang data modeling language simplifies SQL queries by enabling the creation of reusable, intricate data models that incorporate custom columns and dynamic sub-queries. With Git-based version control, analysts can work collaboratively, ensuring that all data models and SQL queries are consistently backed up. The always-free version provides access to a robust BI platform with professional support at no charge. In-database analytics eliminates the need to transfer data to another system, accelerating access and yielding real-time results. The auto-SQL generator intelligently utilizes defined joins in the data model to determine which tables to combine and dynamically generates sub-queries based on the context. Furthermore, the single source of truth data models guarantee that every individual in the organization relies on identical data for their business decisions, fostering consistency and reliability across the board. This comprehensive approach not only enhances collaboration but also solidifies the foundation for smarter strategic planning.