"The main use case for Vize is data analytics and data discovery," co-founder and COO Noureddine Lakehal told me.
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Developers can use GraphQL features for data discovery without having knowledge of the back-end data sources (which is nifty).
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Technologies such as predictive analytics, advanced natural-language generation or smart data discovery solutions can help you attain true value from your data.
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Like most good startup founders confronted with a problem, they decided to solve it themselves by building a data discovery platform for data scientists.
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Services that it covers includes compliance with BCBS 239, CCAR MRAs and GDPR; demonstrating data protection and security; fixing bad data; analytics; and data discovery.
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Among the AI pieces it is including in the platform are advanced machine learning, deep learning, predictive analytics, natural language processing and smart data discovery.
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Einstein AI tools are built in across the platform such as Community Cloud with automated community case escalation and recommended experts, files and groups; Analytics Cloud with smart data discovery and Commerce Cloud with product recommendations.
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Explorium, a data discovery platform for machine learning models, received a couple of unannounced funding rounds over the last year — a $3.6 million seed round last September and a $15.5 million Series A round in March.
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"Data scientists can take advantage of this new AI that fuels deeper data discovery by using Adobe Sensei pre-built models, bringing their existing models or creating custom models from scratch in Experience Platform," the company wrote in the announcement blog post.
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Among those of its bets that have been acquired are the satellite imaging company Skybox, which sold to Google for $500 million last year; and the data discovery and sharing platform 1010data, which sold last August to Conde Nast parent Advance for $500 million.
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The future is having a technology that addresses fundamental data management processes such as data discovery, profiling, standardization, linking and master data management when building and maintaining indexes and reading results data from sources - allowing data analysts to focus on the analysis to gain important insights.
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PKWARE released Smartcrypt, a data protection platform combining encryption, data discovery, and encryption key management, in 2016.
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More recently, PKWARE has focused on enterprise data protection, developing products that integrate data discovery, encryption, and encryption key management. As of , Thompson Street Capital Partners has acquired PKWARE Inc.
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Fuchsine (sometimes spelled fuchsin) or rosaniline hydrochloride is a magenta dye with chemical formula C20H19N3·HCl."Basic chemical data". Discovery Series online database, Developmental Therapeutics Program, U.S. National Institutes of Health. Retrieved on 2007-10-08.
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Optimizing data models, size and processing path/time are ongoing work. As more data is captured at different data stages in not only EIS apps but also other enterprise apps, audio and video tagging can catalyse data discovery.
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DarkShield is a data discovery and masking product designed for protecting data hidden in so-called dark data, or unstructured file, repositories. DarkShield shares the same data searching, classification, and masking functionality with FieldShield and the CellShield Enterprise Edition in IRI Workbench.
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According to The BI Survey 12, a worldwide BI and CPM user survey, the most widely used application areas of Board are reporting, ad-hoc querying, dashboarding, budgeting & planning, OLAP analysis, visual analysis & data discovery, predictive analysis & data mining and financial consolidation (in descending order of use frequency).
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CellShield is a data discovery and masking product designed for protecting data at the cell level in Microsoft Excel spreadsheets. CellShield comes in Personal and Enterprise editions, with the latter capable of finding and remediating PII in multiple files and sheets in drives and folders accessible on a local area network.
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Monarch Experts will help existing Datawatch customers transition to the new Visual Data Discovery platform.PR Newswire, "Datawatch and Monarch Experts Announce Partnership ", 2/21/2014. In March, 2014 Datawatch named Carahsoft Technology as its Master Government Aggregator. Carahsoft, a government IT solutions provider, is now marketing and selling Datawatch’s solutions to the public sector.
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NASDAQ OMX launched MiQ with a partnership with Datawatch.Nasdaq, "NASDAQ OMX Launches MiQ, a New Business Intelligence Product for Global Capital Market Operators", 5/20/2014. In June 2014 Datawatch announced predictive analytics solution with partner Quant5Quant5Yahoo Finance, "Datawatch and Quant5 Team to Bring Predictive Analytics to Real-time Visual Data Discovery", 6/17/2014.
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Power BI provides cloud-based BI (business intelligence) services, known as "Power BI Services", along with a desktop based interface, called "Power BI Desktop". It offers data warehouse capabilities including data preparation, data discovery and interactive dashboards. In March 2016, Microsoft released an additional service called Power BI Embedded on its Azure cloud platform. One main differentiator of the product is the ability to load custom visualizations.
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Wallack was born in Wayzata, Minnesota, a small town outside Minneapolis. She is one of six children. She attended The Breck School and Skidmore College, earning a Bachelor of Arts in English and a Bachelor of Science in business. After college, she returned to Minneapolis, in 1993 where she joined her sister Andrea Wallack in establishing a national presence for NightOwl Discovery, a company specializing in data discovery, governance and compliance for heavily regulated industries.
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Updata Partners also participated in the round. The company previously raised $23.1 million from Updata Partners, Grotech Ventures and Summit Partners, who remain invested in the company. In 2014, Logi Analytics introduced its data discovery product, Logi Vision, to be deployed as a stand-alone application or integrated with its business information platform, Logi Info. Together, these integrated products can be used by customers to address a wide range of analytics use cases across the organisation.
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1991: Datawatch acquired Personics Corporation, a producer of network data access and translation software and video enhancement software. Personics’ principal product was Monarch, a software program that provided data access, translation, and reporting capabilities to users of networked PCs. 1992: Datawatch went public with an IPO.Bloomberg Business Week, Datawatch Corporation 2013: Datawatch acquired Panopticon Software AB, a Swedish software company whose primary product was Panopticon Designer, a visual data discovery application that can create visualizations of streaming real-time data.
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The platform also supports event- driven architectures. Boomi's EDA partners include Dell EMC and Solace as well as vendors specializing in message brokers, event meshes, streaming and pub/sub technology. The platform also offers integrations for Amazon SQS, Microsoft's Azure Service Bus services and Pivotal's RabbitMQ. After Boomi acquired Unifi Software, Boomi incorporated data discovery, catalog and preparation tools into its platform, and continues to offer Unifi as a stand- alone product. In August 2019, Boomi’s iPaaS was authorized by FedRAMP.
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Data Discovery and Query Builder (DDQB) is a data abstraction technology, developed by IBM, that allows users to retrieve information from a data warehouse, in terms of the user's specific area of expertise instead of SQL. DDQB serves the user through a web based graphical user interface and configurable data abstraction model (DAM), which contains both an understanding of the user knowledge domain and the database below it. DDQB uses a set of Eclipse-based customization tooling and can be deployed as a set of Web Services.
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Besides metagenome analysis, MG-RAST can also be used for data discovery. The visualization or comparison of metagenomes profiles and data sets can be implemented in a wide variety of modes; the web interface allows to select data based on criteria like composition, sequences quality, functionality or sample type and offers several ways to compute statistical inferences and ecological analyses. The profiles for the metagenomes can be visualized and compared by using barcharts, trees, spreadsheet-like tables, heatmaps, PCoA, rarefaction plots, circular recruitment plot, and KEGG maps.
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Today, FWS serves its data via an on-line data discovery "Wetlands Mapper". GIS users can access wetlands data through an online wetland mapping service or download data for various applications (maps, data analyses, and reports). The techniques used by NWI have recently been adopted by the Federal Geographic Data Committee as the federal wetland mapping standard (FGDC Wetlands Subcommittee 2009). This standard applies to all federal grants involving wetland mapping to insure the data can be added to the Wetlands Layer of the National Spatial Data Infrastructure.
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Mercury Metadata Search System Mercury is a distributed metadata management, data discovery and access system. It is a scientific data search system to capture and manage biogeochemical and ecological data in support of the Earth science programs funded by the United States Department of Energy (DOE) and United States Geological Survey (USGS) - Department of Interior (DOI). Mercury was originally developed for NASA, but the consortium is now supported by USGS and the DOE. Ongoing development of Mercury is done through an informal consortium at Oak Ridge National Laboratory.
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On all supported platforms, programs written in the language of SAS can be executed from a WPS command line interface, often referred to as running in batch mode. WPS can also be used from a graphical user interface known as the WPS Workbench for managing, editing and running programs written in the language of SAS. The WPS Workbench user interface is based on Eclipse. WPS version 4 (released in March 2018) introduced a drag-and-drop workflow canvas providing interactive blocks for data retrieval, blending and preparation, data discovery and profiling, predictive modelling powered by machine learning algorithms, model performance validation and scorecards.
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The time tagging of both the data and metadata allows precise determination of the state of a system, and therefore whether its data is of interest, regardless of whether that system remains static or has elements removed, replaced or added. This permits searching for data at a finer granularity than previously possible, while still supporting higher-level data discovery if a user so desires, since the use of individual fields within a TML system description is optional. TML can process data from simple stationary in-situ transducers to high bandwidth dynamic remote devices such as a synthetic aperture radar system.
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Whether being regulated or self regulated, the laws require to establish ways at which access to sensitive information is limited to the people with different roles, thus in essence requiring establishment of the "sensitive data domain" model"Sensitive Data Discovery" and mechanisms of its protection. Some of the domains have a guideline in form of pre-defined models such as "Safe Harbor" of HIPAA, based on the research of Latanya Sweeny and established privacy industry metrics. Additionally, many other countries have enacted their own legislature regarding data privacy protection, and more are still in the process of doing so."International Privacy Laws " InformationShield.
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The user, rather than the database itself, typically initiates data curation and maintains metadata. According to the University of Illinois' Graduate School of Library and Information Science, "Data curation is the active and on-going management of data through its lifecycle of interest and usefulness to scholarship, science, and education; curation activities enable data discovery and retrieval, maintain quality, add value, and provide for re- use over time." The data curation workflow is distinct from data quality management, data protection, lifecycle management and data movement. Census data has been available in tabulated punch card form since the early 20th century and has been electronic since the 1960s.
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The NERC Science Information Strategy (SIS) was created to provide the framework for NERC to work more closely and effectively with its scientific communities, both internal and external, in delivering data and information management services to support its five-year science strategy, the Next Generation Science for Planet Earth 2007-2012. The Science Information Strategy is being implemented in three phases, beginning April 2010. Each of these phases will be made up of a number of smaller projects. Project/Phase 1 will concentrate on determining user requirements, documenting existing holdings, agreeing an information architecture, updating the NERC Data Policy and improving the data discovery tools.
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According to Gartner, while Paxata is an early entrant into the market, many startups and large corporations are making investments in developing similar competing products. According to Gigaom and IT Business Edge, one way Paxata differs is that it automatically merges multiple data-sets into a single table, so it can be easily imported into a visualization or analysis tool. Gartner said Paxata will have a difficult time finding a compelling pricing model, when many data discovery tools that it supplements provide some similar features. In contrast, Ventana said Paxata's pricing was "a pretty small amount" compared to the amount of time users can save.
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OpenID Connect is a simple identity layer on top of the OAuth 2.0 protocol, which allows computing clients to verify the identity of an end-user based on the authentication performed by an authorization server, as well as to obtain basic profile information about the end-user in an interoperable and REST-like manner. In technical terms, OpenID Connect specifies a RESTful HTTP API, using JSON as a data format. OpenID Connect allows a range of kinds of clients, including Web-based, mobile, and JavaScript clients, to request and receive information about authenticated sessions and end-users. The specification suite is extensible, supporting optional features such as encryption of identity data, discovery of OpenID Providers, and session management.
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The building was designed for, and is primarily used by, the Information Technology Leadership program. This academic discipline studies the traditional Information Technology field as a liberal art, where the core principles and interdisciplinary connections of the field are examined. Students in this program take a standard curriculum, augmented with focused study in one of 4 possible fields: computer science, data discovery, information systems, and new media technologies. In 2002, Pennsylvania Congressman and former student John Murtha, who was a long-time chair of the House Appropriations Defense Subcommittee, procured a $2.7 million defense appropriation for the Information Technology Leadership program to develop a remote educational program to would train members of the National Guard in technology skills, ranging from basic computer literacy to advanced applications.
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Astroinformatics is primarily focused on developing the tools, methods, and applications of computational science, data science, machine learning, and statistics for research and education in data-oriented astronomy. Early efforts in this direction included data discovery, metadata standards development, data modeling, astronomical data dictionary development, data access, information retrieval, data integration, and data mining in the astronomical Virtual Observatory initiatives. Further development of the field, along with astronomy community endorsement, was presented to the National Research Council (United States) in 2009 in the Astroinformatics "State of the Profession" Position Paper for the 2010 Astronomy and Astrophysics Decadal Survey. That position paper provided the basis for the subsequent more detailed exposition of the field in the Informatics Journal paper Astroinformatics: Data-Oriented Astronomy Research and Education.
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MarketWatch, "Datawatch Names Carahsoft Master Government Aggregator", 3/3/2014. March, 2014 - Datawatch announced its global partnership with OSIsoft and the release of its real-time data connector to the PI System.OSIsoft PI System In April, 2014 Datawatch integrated its software with Cloudant's NoSQL database-as-a-service DBaaS.Yahoo Finance, "Datawatch Delivers Visual Data Discovery to NoSQL Cloud DBaaS", 4/22/2014 In May, 2014 Datawatch announced a Global Relationship with Informatica,Yahoo Finance, "Datawatch Announces Global Relationship with Informatica", 5/8/2014. as well as support for IBM Cognos TM1Yahoo Finance, "Datawatch to Demonstrate Support for Latest IBM® Cognos® TM1 at Visions 2014 Conference", 5/8/2014. and a Global Strategic Alliance with PerceptivePerceptiveYahoo Finance, "Datawatch Announces Global Strategic Alliance with Perceptive To Enhance Analytics for Content Management Solution", 5/9/2014.
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UNSDI is an initiative of the United Nations Geographic Information Working Group (UNGIWG), a voluntary network of UN professionals working in the fields of cartography and geographic information science. UNSDI aims to contribute to the mission of the United Nations, from to peacekeeping to humanitarian relief, from climate change to disaster reduction, response and recovery, from environmental protection to poverty reduction, food security, water management and economic development and to contribute to the realization of the UN Millennium Development Goals. By facilitating efficient global and local access, exchange and utilization of geospatial information, UNSDI will make the United Nations system more effective and support its “Delivering as One” policies. Spatial data infrastructures provide the institutional and technical foundation of policies, standards and procedures that enable organizations and information systems to interact in a way that facilitates spatial data discovery, evaluation and applications.
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The FBI contended that Microsoft had full control of the data and should be compelled to turn it over in response to the warrant, but Microsoft argued that the SCA did not cover data stored outside the United States. The challenge identified that while the FBI could request a mutual legal assistance treaty (MLAT) to aid in data discovery during cross- border law enforcement, the process to acquire a new MLAT if one is not in place, or to process a request through an existing MLAT, can be slow and impede law enforcement efforts. Congress, primarily led by Senator Orrin Hatch, had attempted to create legislation prior to the CLOUD Act to amend the SCA with the concerns of Microsoft and other technologies companies with respect to foreign privacy rights. The "Law Enforcement Access to Data Stored Abroad Act" (LEADS Act) in 2015 and the International Communications Privacy Act (ICPA) in 2017 were both previous bills intended to amend the SCA but which failed to gain passage.
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Service Layer for multivendor interoperability. The architecture standardised by oneM2M defines an IoT Service Layer, i.e. a vendor-independent software Middleware between processing and communication hardware and IoT applications providing a set of functions commonly needed by IoT applications. The oneM2M Service Layer provides use case-independent functions. • oneM2M Common Service layer Functions (CSF’s) provide proper: • Identification of users and applications • Authentication and authorisation of users and applications • End-to-end data encryption • Remote provisioning and service activation • Device management • Connectivity setup and data transmission scheduling • Data aggregation, buffering in case of missing connectivity and synchronisation upon connectivity re-establishment • Group management and application and data discovery functions The functions listed above provided by the oneM2M common service layer, are exposed and controlled via globally standardized vendor-independent and uniform APIs, towards the IoT applications. IoT applications or more generically “Application Entities” AE’s are generic terms for applications executed in so-called Application Dedicated Nodes ADNs or Middle Nodes MNs and at the Infrastructure Node IN. Applications (AEs) at the device (ADN, MN) and the Infrastructure Platform (IN) are separated by the oneM2M APIs from the actual oneM2M Common Service functions (CSFs) like the ones listed above.
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