[{"innerBlocks":[],"name":"core\/freeform","postId":127382,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"

22 top analytics and business intelligence platforms<\/h2>
Qlik, Tableau, ThoughtSpot and Microsoft are among the top providers of analytics and business intelligence platforms, according to a new Gartner study.<\/p>

About these analytics and BI platforms<\/h2>
Gartner Research has released its latest Magic Quadrant report, looking at the top providers of analytics and business intelligence software. The report was written by Gartner analysts Cindi Howson, James Richardson, Rita Sallam and Austin Kronz. It breaks down the top players into four categories\u2014leaders, challengers, visionaries and niche players, depending on the strength of each in the marketplace.<\/p>

The leaders<\/h2>
\u201cLeaders demonstrate a solid understanding of the product capabilities and commitment to customer success that buyers in this market demand,\u201d the analysts explain. \u201cThey couple this understanding with an easily comprehensible and attractive pricing model that supports proof of value, incremental purchases and enterprise scale. In the modern analytics and BI platform market, buying decisions are being made, or at least heavily influenced, by business users that demand products that are easy to buy and use. They require that these products deliver clear business value and enable use of powerful analytics by those with limited technical expertise and without upfront involvement from the IT department or technical experts.\u201d<\/p>

Microsoft<\/h2>
\u201cMicrosoft offers data preparation, visual-based data discovery, interactive dashboards and augmented analytics via a single product, Power BI,\u201d the analysts explain. \u201cIt is available as a SaaS option running in the Azure cloud or as an on-premises option in Power BI Report Server. Power BI Desktop can be used as a stand-alone, free personal analysis tool. It is also required when power users are authoring complex data mashups involving on-premises data sources.\u201d<\/p>

Qlik<\/h2>
\u201cQlik delivers governed data discovery and agile analytics and BI via its lead product, Qlik Sense, which is built on the Qlik Analytics Platform,\u201d the analysts explain. \u201cThe platform can be used to build customized applications via an extensive set of APIs to support the embedded analytics use case. Qlik\u2019s original product, QlikView, accounts for a large portion of the company\u2019s installed base, but Qlik Sense now generates more than 67 percent of its license revenue.\u201d<\/p>

Tableau<\/h2>
\u201cTableau offers an intuitive, interactive, visual-based exploration experience that enables business users to access, prepare, analyze and present findings in their data without technical skills or coding,\u201d the analysts explain. \u201cTableau\u2019s offering is primarily deployed on-premises, either as a stand-alone desktop application or integrated with a server for sharing content; Tableau Online is the cloud-based SaaS offering.\u201d<\/p>

ThoughtSpot<\/h2>
\u201cThoughtSpot differentiates itself on its search-based interface with augmented analytics at scale,\u201d the analysts explain. \u201cThe company was founded by former Google executives, and received an additional round of series D funding in 2018 of $145 million, bringing its total funding to $306 million. ThoughtSpot\u2019s software can be deployed in the cloud or as an on-premises appliance on commodity hardware, with data loaded in-memory into a massively parallel processing (MPP) engine and indexed for fast query performance.\u201d<\/p>

Challengers<\/h2>
\u201cChallengers are well-positioned to succeed in this market,\u201d the analysts say. \u201cHowever, they may be limited to specific use cases, technical environments or application domains. Their vision may be hampered by the lack of a coordinated strategy across various products in their platform portfolio. Alternatively, they may fall short of the Leaders in terms of effective marketing, sales channels, geographic presence, industry-specific content and innovation.\u201d<\/p>

MicroStrategy<\/h2>
\u201cMicroStrategy received among the highest product scores in this Magic Quadrant, both overall and for all evaluated use cases,\u201d the analysts note. \u201cIt offers best-in-class enterprise reporting and mobile capabilities, delivered in a single, fully integrated platform and workflow. This makes MicroStrategy better-suited to large-scale SOR reporting and governed data discovery deployments for large and complex datasets than most other vendors in this Magic Quadrant.\u201d<\/p>

Visionaries<\/h2>
\u201cVisionaries have a strong and unique vision for delivering a modern analytics and BI platform,\u201d the analysts write. \u201cThey offer deep functionality in the areas they address. However, they may have gaps when it comes to fulfilling broader functionality requirements or lower scores for customer experience, operations and sales execution. Visionaries are thought leaders and innovators, but they may be lacking in scale or there may be concerns about their ability to grow and still provide consistent execution.\u201d<\/p>

Salesforce<\/h2>
\u201cIntegration of the AI-driven augmented analytics capabilities in Einstein Discovery with the rest of the Salesforce Analytics portfolio has disrupted the market in a way that other vendors are trying to emulate,\u201d the analysts say. \u201cSalesforce continues to invest in augmented analytics innovations in the field of data preparation, and in conversational analytics, and proactive alerting is on its roadmap. To build trust from automatically generated insights, Einstein Analytics exposes the key drivers of insights to users.\u201d<\/p>

SAP<\/h2>
\u201cSmart Insights\u2014new ML-driven functions, including NLP-based search\u2014make SAP Analytics Cloud one of the highest rated platforms for augmented data discovery capability. Further, SAP Analytics Hub is intended to bridge cloud and on-premises deployments, providing a single front end for SAP and partner-originated analytic offerings. This vision is resonating\u2014reference customers for SAP Analytics Cloud showed a bigger improvement in their view of their vendor\u2019s viability than any other group of reference customers surveyed for this Magic Quadrant.\u201d<\/p>

SAS<\/h2>
\u201cSAS Visual Analytics has some of the highest critical capability ratings for both agile, centralized BI provisioning and decentralized analytics,\u201d the analysts say. \u201cAs a server-based platform, it provides governance and scalability with an open architecture that includes Hadoop Distributed File System (HDFS) and Direct Network File System (DNFS) for persistence and its own in-memory engine for fast performance. The menu-driven advanced analytics, with open models, remains a competitive differentiator, as does the support for IoT and real-time data.\u201d<\/p>

Sisense<\/h2>
\u201cSisense enables customers to ingest data from a range of data sources, while also cleansing and transforming the data,\u201d the analysts write. \u201cData can optionally be left in-database for some high-performing databases, or brought into the Sisense ElastiCube\u2014the vendor\u2019s proprietary caching engine that uses both in-memory and in-chip processing for fast performance. It is noteworthy, therefore, that Sisense had the highest percentage of reference customers with no data warehouse (13 percent).\u201d<\/p>

TIBCO Software<\/h2>
\u201cTIBCO Software was an early visual-based data discovery disruptor with Spotfire, which helped shift the market from traditional reporting to modern analytics and BI,\u201d the analysts explain. \u201cSpotfire offers extensive capabilities for analytics dashboards, interactive visualization and data preparation in a single design tool and workflow. It also offers flexible processing options, either in-memory or in-database. Through acquisitions and OEM relationships, TIBCO has continued to expand its capabilities to include data science, ML and streaming analytics, location intelligence, data cataloging and data virtualization.\u201d<\/p>

Niche players<\/h2>
\u201cNiche Players do well in a specific segment of the analytics and BI market\u2014such as cloud BI, customer-facing analytics, agile reporting and dashboarding, or embeddability\u2014or have limited ability to surpass other vendors in terms of innovation or performance,\u201d the analysts explain. \u201cThey may focus on a specific domain or aspect of analytics and BI, but are likely to lack deep functionality elsewhere. They may also have gaps in terms of broader platform functionality, or have less-than-stellar customer feedback.\u201d<\/p>

Birst<\/h2>
\u201cBirst provides data preparation, dashboards, visual exploration and formatted, scheduled reports on a single platform,\u201d the analysts write. \u201cFew other vendors support both usage styles in this way. The networked semantic layer enables business units to create data models that can then be promoted to the enterprise. A new orchestration capability enables this content to be replicated to multiple instances. Birst supports live connectivity to on-premises data sources. However, its rapid creation of a data model and all-in-one data warehouse that can draw on a range of storage options (Microsoft SQL Server Analysis Services, SAP HANA, Amazon Redshift) is a unique selling point.\u201d<\/p>

BOARD International<\/h2>
\u201cBOARD is one of only two vendors offering a modern analytics and BI platform with integrated financial planning and reporting functionality (the other being SAP, with SAP Analytics Cloud),\u201d the analysts note. \u201cAs such, it is highly differentiated for the relatively small number of buyers looking to close the gap between BI and financial processes. BOARD is also used for read-only analytics and BI deployments, although, in Gartner\u2019s view, this is less commonly the case. BOARD\u2019s new self-service reporting capabilities strengthen its Mode 1 support.\u201d<\/p>

Domo<\/h2>
\u201cDomo offers rapid deployment of intuitive dashboards,\u201d the analysts say. \u201cIts cloud-native approach, aided by an extensive range of prebuilt connectors to cloud-based data sources and applications, feeds Domo Apps, which are out-of-the-box content packs with KPIs and dashboards (available in both free and premium versions). Domo\u2019s ability to connect to enterprise applications is a differentiator in that Domo maintains the connectors in the form of API-like connectors that can respond dynamically to changes in source-side schemas.\u201d<\/p>

GoodData<\/h2>
\u201cGoodData offers a comprehensive, multi-tenant, cloud-only platform focused on embedded analytics for use at scale,\u201d according to the analysts. \u201cThe GoodData Enterprise Insights Platform includes data integration and data storage capabilities, an analytics engine, integration with a wide variety of data science and ML technologies, and a front-end presentation layer called Analytical Designer. GoodData differentiates itself by its ability to embed analytics directly into customers\u2019 business processes or external customer-facing analytic applications.\u201d<\/p>

IBM<\/h2>
\u201cOrganizations\u2019 desire to modernize their traditional BI portfolios has often led them to use multiple BI tools for distinct purposes,\u201d the analysts explain. \u201cIBM Cognos Analytics 11.1 is one of the few offerings that includes enterprise reporting, governed and self-service visual exploration and augmented analytics in a single platform. In addition, as existing IBM Cognos Framework Manager models and reports from earlier versions can be leveraged in the single environment, there is a migration path and the ability to use existing content.\u201d<\/p>

Information Builders<\/h2>
\u201cInformation Builders sells the integrated WebFOCUS analytics and BI platform, as well as individual components thereof,\u201d the analysts say. \u201cWebFOCUS Designer (formerly InfoAssist+) includes components from the WebFOCUS stack that are intended to satisfy modern self-service analytics and BI needs. Over half (56 percent) the company\u2019s reference customers reported that they use the platform for decentralized analytics, and 44 percent for agile, centralized BI provisioning.\u201d<\/p>

Logi Analytics<\/h2>
\u201cLogi Analytics focuses solely on embedded analytics,\u201d the analysts note. \u201cThe Logi Analytics Platform offers a set of capabilities to help software product managers and developers build embeddable analytic apps, and a self-service module to help business users create and interact with dashboards and data visualizations. DataHub is used to ingest, blend and enrich data from multiple sources. The majority (61 percent) of Logi\u2019s reference customers use it for OEM or embedded analytics. More than one-fifth (21 percent) use it for extranet deployment.\u201d<\/p>

Looker<\/h2>
\u201cLooker\u2019s key differentiator is native support for cloud-based analytic databases, particularly Amazon (Redshift, Athena), Google BigQuery and Snowflake,\u201d the analysts say. \u201cWhereas most competing tools use their own in-memory, columnar storage, Looker always uses the database for processing and mashups. LookML is a browser-based, SQL-like modeling language for power users. Its data scalability is in the top tier, with 36 percent of Looker\u2019s reference customers analyzing more than 1 terabyte of data and a median of 585 million row tables.\u201d<\/p>

Oracle<\/h2>
\u201cOracle offers a broad range of analytics and BI capabilities, both in the Oracle Cloud and on-premises,\u201d the analysts explain. \u201cThe modern components of Oracle Analytics Cloud (OAC) are the focus of this Magic Quadrant. OAC includes integrated data preparation, data discovery (with advanced exploration and augmented analytics) and interactive dashboards. Oracle Data Visualization Desktop is available as a free download for personal use. OAC is primarily deployed by its reference customers for agile, centralized BI provisioning (58 percent) and decentralized analytics (72 percent) use cases.\u201d<\/p>

Pyramid Analytics<\/h2>
\u201cPyramid supports agile workflows and governed, report-centric content within a single platform and interface,\u201d the analysts explain. \u201cThe solution is well-suited to governed data discovery, with features such as BI content watermarking, reusability and sharing of datasets, metadata management and data lineage. Reports and dashboards support scheduling and distribution, alerting and discussions\u2014Mode 1 reporting capabilities that are often lacking in competing products.\u201d<\/p>

Yellowfin<\/h2>
\u201cYellowfin\u2019s single platform includes one of the broadest ranges of capabilities, spanning data preparation, reporting with scheduled distributions, visual exploration and augmented analytics,\u201d the analysts explain. \u201cReports, dashboards and administration are all accessed via a browser-based interface, with no desktop components. Data is usually queried live from a relational data source, as caching into the columnar, in-memory engine is optional.\u201d<\/p>

","saveContent":"

22 top analytics and business intelligence platforms<\/h2>
Qlik, Tableau, ThoughtSpot and Microsoft are among the top providers of analytics and business intelligence platforms, according to a new Gartner study.<\/p>

About these analytics and BI platforms<\/h2>
Gartner Research has released its latest Magic Quadrant report, looking at the top providers of analytics and business intelligence software. The report was written by Gartner analysts Cindi Howson, James Richardson, Rita Sallam and Austin Kronz. It breaks down the top players into four categories\u2014leaders, challengers, visionaries and niche players, depending on the strength of each in the marketplace.<\/p>

The leaders<\/h2>
\u201cLeaders demonstrate a solid understanding of the product capabilities and commitment to customer success that buyers in this market demand,\u201d the analysts explain. \u201cThey couple this understanding with an easily comprehensible and attractive pricing model that supports proof of value, incremental purchases and enterprise scale. In the modern analytics and BI platform market, buying decisions are being made, or at least heavily influenced, by business users that demand products that are easy to buy and use. They require that these products deliver clear business value and enable use of powerful analytics by those with limited technical expertise and without upfront involvement from the IT department or technical experts.\u201d<\/p>

Microsoft<\/h2>
\u201cMicrosoft offers data preparation, visual-based data discovery, interactive dashboards and augmented analytics via a single product, Power BI,\u201d the analysts explain. \u201cIt is available as a SaaS option running in the Azure cloud or as an on-premises option in Power BI Report Server. Power BI Desktop can be used as a stand-alone, free personal analysis tool. It is also required when power users are authoring complex data mashups involving on-premises data sources.\u201d<\/p>

Qlik<\/h2>
\u201cQlik delivers governed data discovery and agile analytics and BI via its lead product, Qlik Sense, which is built on the Qlik Analytics Platform,\u201d the analysts explain. \u201cThe platform can be used to build customized applications via an extensive set of APIs to support the embedded analytics use case. Qlik\u2019s original product, QlikView, accounts for a large portion of the company\u2019s installed base, but Qlik Sense now generates more than 67 percent of its license revenue.\u201d<\/p>

Tableau<\/h2>
\u201cTableau offers an intuitive, interactive, visual-based exploration experience that enables business users to access, prepare, analyze and present findings in their data without technical skills or coding,\u201d the analysts explain. \u201cTableau\u2019s offering is primarily deployed on-premises, either as a stand-alone desktop application or integrated with a server for sharing content; Tableau Online is the cloud-based SaaS offering.\u201d<\/p>

ThoughtSpot<\/h2>
\u201cThoughtSpot differentiates itself on its search-based interface with augmented analytics at scale,\u201d the analysts explain. \u201cThe company was founded by former Google executives, and received an additional round of series D funding in 2018 of $145 million, bringing its total funding to $306 million. ThoughtSpot\u2019s software can be deployed in the cloud or as an on-premises appliance on commodity hardware, with data loaded in-memory into a massively parallel processing (MPP) engine and indexed for fast query performance.\u201d<\/p>

Challengers<\/h2>
\u201cChallengers are well-positioned to succeed in this market,\u201d the analysts say. \u201cHowever, they may be limited to specific use cases, technical environments or application domains. Their vision may be hampered by the lack of a coordinated strategy across various products in their platform portfolio. Alternatively, they may fall short of the Leaders in terms of effective marketing, sales channels, geographic presence, industry-specific content and innovation.\u201d<\/p>

MicroStrategy<\/h2>
\u201cMicroStrategy received among the highest product scores in this Magic Quadrant, both overall and for all evaluated use cases,\u201d the analysts note. \u201cIt offers best-in-class enterprise reporting and mobile capabilities, delivered in a single, fully integrated platform and workflow. This makes MicroStrategy better-suited to large-scale SOR reporting and governed data discovery deployments for large and complex datasets than most other vendors in this Magic Quadrant.\u201d<\/p>

Visionaries<\/h2>
\u201cVisionaries have a strong and unique vision for delivering a modern analytics and BI platform,\u201d the analysts write. \u201cThey offer deep functionality in the areas they address. However, they may have gaps when it comes to fulfilling broader functionality requirements or lower scores for customer experience, operations and sales execution. Visionaries are thought leaders and innovators, but they may be lacking in scale or there may be concerns about their ability to grow and still provide consistent execution.\u201d<\/p>

Salesforce<\/h2>
\u201cIntegration of the AI-driven augmented analytics capabilities in Einstein Discovery with the rest of the Salesforce Analytics portfolio has disrupted the market in a way that other vendors are trying to emulate,\u201d the analysts say. \u201cSalesforce continues to invest in augmented analytics innovations in the field of data preparation, and in conversational analytics, and proactive alerting is on its roadmap. To build trust from automatically generated insights, Einstein Analytics exposes the key drivers of insights to users.\u201d<\/p>

SAP<\/h2>
\u201cSmart Insights\u2014new ML-driven functions, including NLP-based search\u2014make SAP Analytics Cloud one of the highest rated platforms for augmented data discovery capability. Further, SAP Analytics Hub is intended to bridge cloud and on-premises deployments, providing a single front end for SAP and partner-originated analytic offerings. This vision is resonating\u2014reference customers for SAP Analytics Cloud showed a bigger improvement in their view of their vendor\u2019s viability than any other group of reference customers surveyed for this Magic Quadrant.\u201d<\/p>

SAS<\/h2>
\u201cSAS Visual Analytics has some of the highest critical capability ratings for both agile, centralized BI provisioning and decentralized analytics,\u201d the analysts say. \u201cAs a server-based platform, it provides governance and scalability with an open architecture that includes Hadoop Distributed File System (HDFS) and Direct Network File System (DNFS) for persistence and its own in-memory engine for fast performance. The menu-driven advanced analytics, with open models, remains a competitive differentiator, as does the support for IoT and real-time data.\u201d<\/p>

Sisense<\/h2>
\u201cSisense enables customers to ingest data from a range of data sources, while also cleansing and transforming the data,\u201d the analysts write. \u201cData can optionally be left in-database for some high-performing databases, or brought into the Sisense ElastiCube\u2014the vendor\u2019s proprietary caching engine that uses both in-memory and in-chip processing for fast performance. It is noteworthy, therefore, that Sisense had the highest percentage of reference customers with no data warehouse (13 percent).\u201d<\/p>

TIBCO Software<\/h2>
\u201cTIBCO Software was an early visual-based data discovery disruptor with Spotfire, which helped shift the market from traditional reporting to modern analytics and BI,\u201d the analysts explain. \u201cSpotfire offers extensive capabilities for analytics dashboards, interactive visualization and data preparation in a single design tool and workflow. It also offers flexible processing options, either in-memory or in-database. Through acquisitions and OEM relationships, TIBCO has continued to expand its capabilities to include data science, ML and streaming analytics, location intelligence, data cataloging and data virtualization.\u201d<\/p>

Niche players<\/h2>
\u201cNiche Players do well in a specific segment of the analytics and BI market\u2014such as cloud BI, customer-facing analytics, agile reporting and dashboarding, or embeddability\u2014or have limited ability to surpass other vendors in terms of innovation or performance,\u201d the analysts explain. \u201cThey may focus on a specific domain or aspect of analytics and BI, but are likely to lack deep functionality elsewhere. They may also have gaps in terms of broader platform functionality, or have less-than-stellar customer feedback.\u201d<\/p>

Birst<\/h2>
\u201cBirst provides data preparation, dashboards, visual exploration and formatted, scheduled reports on a single platform,\u201d the analysts write. \u201cFew other vendors support both usage styles in this way. The networked semantic layer enables business units to create data models that can then be promoted to the enterprise. A new orchestration capability enables this content to be replicated to multiple instances. Birst supports live connectivity to on-premises data sources. However, its rapid creation of a data model and all-in-one data warehouse that can draw on a range of storage options (Microsoft SQL Server Analysis Services, SAP HANA, Amazon Redshift) is a unique selling point.\u201d<\/p>

BOARD International<\/h2>
\u201cBOARD is one of only two vendors offering a modern analytics and BI platform with integrated financial planning and reporting functionality (the other being SAP, with SAP Analytics Cloud),\u201d the analysts note. \u201cAs such, it is highly differentiated for the relatively small number of buyers looking to close the gap between BI and financial processes. BOARD is also used for read-only analytics and BI deployments, although, in Gartner\u2019s view, this is less commonly the case. BOARD\u2019s new self-service reporting capabilities strengthen its Mode 1 support.\u201d<\/p>

Domo<\/h2>
\u201cDomo offers rapid deployment of intuitive dashboards,\u201d the analysts say. \u201cIts cloud-native approach, aided by an extensive range of prebuilt connectors to cloud-based data sources and applications, feeds Domo Apps, which are out-of-the-box content packs with KPIs and dashboards (available in both free and premium versions). Domo\u2019s ability to connect to enterprise applications is a differentiator in that Domo maintains the connectors in the form of API-like connectors that can respond dynamically to changes in source-side schemas.\u201d<\/p>

GoodData<\/h2>
\u201cGoodData offers a comprehensive, multi-tenant, cloud-only platform focused on embedded analytics for use at scale,\u201d according to the analysts. \u201cThe GoodData Enterprise Insights Platform includes data integration and data storage capabilities, an analytics engine, integration with a wide variety of data science and ML technologies, and a front-end presentation layer called Analytical Designer. GoodData differentiates itself by its ability to embed analytics directly into customers\u2019 business processes or external customer-facing analytic applications.\u201d<\/p>

IBM<\/h2>
\u201cOrganizations\u2019 desire to modernize their traditional BI portfolios has often led them to use multiple BI tools for distinct purposes,\u201d the analysts explain. \u201cIBM Cognos Analytics 11.1 is one of the few offerings that includes enterprise reporting, governed and self-service visual exploration and augmented analytics in a single platform. In addition, as existing IBM Cognos Framework Manager models and reports from earlier versions can be leveraged in the single environment, there is a migration path and the ability to use existing content.\u201d<\/p>

Information Builders<\/h2>
\u201cInformation Builders sells the integrated WebFOCUS analytics and BI platform, as well as individual components thereof,\u201d the analysts say. \u201cWebFOCUS Designer (formerly InfoAssist+) includes components from the WebFOCUS stack that are intended to satisfy modern self-service analytics and BI needs. Over half (56 percent) the company\u2019s reference customers reported that they use the platform for decentralized analytics, and 44 percent for agile, centralized BI provisioning.\u201d<\/p>

Logi Analytics<\/h2>
\u201cLogi Analytics focuses solely on embedded analytics,\u201d the analysts note. \u201cThe Logi Analytics Platform offers a set of capabilities to help software product managers and developers build embeddable analytic apps, and a self-service module to help business users create and interact with dashboards and data visualizations. DataHub is used to ingest, blend and enrich data from multiple sources. The majority (61 percent) of Logi\u2019s reference customers use it for OEM or embedded analytics. More than one-fifth (21 percent) use it for extranet deployment.\u201d<\/p>

Looker<\/h2>
\u201cLooker\u2019s key differentiator is native support for cloud-based analytic databases, particularly Amazon (Redshift, Athena), Google BigQuery and Snowflake,\u201d the analysts say. \u201cWhereas most competing tools use their own in-memory, columnar storage, Looker always uses the database for processing and mashups. LookML is a browser-based, SQL-like modeling language for power users. Its data scalability is in the top tier, with 36 percent of Looker\u2019s reference customers analyzing more than 1 terabyte of data and a median of 585 million row tables.\u201d<\/p>

Oracle<\/h2>
\u201cOracle offers a broad range of analytics and BI capabilities, both in the Oracle Cloud and on-premises,\u201d the analysts explain. \u201cThe modern components of Oracle Analytics Cloud (OAC) are the focus of this Magic Quadrant. OAC includes integrated data preparation, data discovery (with advanced exploration and augmented analytics) and interactive dashboards. Oracle Data Visualization Desktop is available as a free download for personal use. OAC is primarily deployed by its reference customers for agile, centralized BI provisioning (58 percent) and decentralized analytics (72 percent) use cases.\u201d<\/p>

Pyramid Analytics<\/h2>
\u201cPyramid supports agile workflows and governed, report-centric content within a single platform and interface,\u201d the analysts explain. \u201cThe solution is well-suited to governed data discovery, with features such as BI content watermarking, reusability and sharing of datasets, metadata management and data lineage. Reports and dashboards support scheduling and distribution, alerting and discussions\u2014Mode 1 reporting capabilities that are often lacking in competing products.\u201d<\/p>

Yellowfin<\/h2>
\u201cYellowfin\u2019s single platform includes one of the broadest ranges of capabilities, spanning data preparation, reporting with scheduled distributions, visual exploration and augmented analytics,\u201d the analysts explain. \u201cReports, dashboards and administration are all accessed via a browser-based interface, with no desktop components. Data is usually queried live from a relational data source, as caching into the columnar, in-memory engine is optional.\u201d<\/p>

","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

22 top analytics and business intelligence platforms<\/h2>Qlik, Tableau, ThoughtSpot and Microsoft are among the top providers of analytics and business intelligence platforms, according to a new Gartner study.<\/p>

22 top analytics and business intelligence platforms<\/h2>Qlik, Tableau, ThoughtSpot and Microsoft are among the top providers of analytics and business intelligence platforms, according to a new Gartner study.<\/p>

22 top analytics and business intelligence platforms<\/h2>
Qlik, Tableau, ThoughtSpot and Microsoft are among the top providers of analytics and business intelligence platforms, according to a new Gartner study.<\/p>

22 top analytics and business intelligence platforms<\/h2>
Qlik, Tableau, ThoughtSpot and Microsoft are among the top providers of analytics and business intelligence platforms, according to a new Gartner study.<\/p>

22 top analytics and business intelligence platforms

More for you