{"id":3620,"date":"2021-09-27T11:14:56","date_gmt":"2021-09-27T16:14:56","guid":{"rendered":"https:\/\/inova8.com\/bg_inova8.com\/?p=3620"},"modified":"2021-09-27T11:14:56","modified_gmt":"2021-09-27T16:14:56","slug":"the-intelligentgraph-way-or-the-groundhog-way-to-efficient-data-analytics","status":"publish","type":"post","link":"https:\/\/inova8.com\/bg_inova8.com\/the-intelligentgraph-way-or-the-groundhog-way-to-efficient-data-analytics\/","title":{"rendered":"The IntelligentGraph-way or the Groundhog-way to efficient data analytics"},"content":{"rendered":"
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The IntelligentGraph-way or the Groundhog-way to efficient data analytics.pdf<\/a><\/span><\/p>\r\n

Data is rather like poor red wine: it neither travels nor ages well. IntelligentGraph avoids data traveling by moving analysis into the knowledge graph rather than moving data to the analysis engine, obsoleting the groundhog-analysis-way<\/span><\/p>\r\n

Solving data analysis, the IntelligentGraph-way<\/span><\/h2>\r\n

Data is streamed to the IntelligentGraph datastore, and then analysis\/calculation nodes are added to that graph which is accessible to all and by all applications.<\/span><\/p>\r\n

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The IntelligentGraph-way of data-analysis is to:<\/span><\/p>\r\n

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  • Extract-Load (losslessly) the source data into an Intelligent Knowledge Graph<\/span><\/li>\r\n
  • Add analysis\/calculation nodes to the KnowledgeGraph which calculate additional analysis values, aggregations, etc.<\/span><\/li>\r\n
  • Report results, using any standard reporting tool<\/span><\/li>\r\n
  • Add more analysis\/calculation nodes as additional requests come through. These new calculations can refer to the existing results<\/span><\/li>\r\n
  • \u2026 relax, you\u2019ve become the star data analyst:-)<\/span><\/li>\r\n<\/ul>\r\n

    Solving data analysis, the Groundhog-way<\/span><\/h2>\r\n

    Data is in the operational data-sources, data is staged in a data-warehouse\/mart\/lake, then the analysis is done by the analysis engine (aka Excel), right? And like poor red wine, constantly moving data damages it.<\/span><\/p>\r\n

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    The Groundhog-way of data analysis is to:<\/span><\/p>\r\n

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    • Extract-Transform(aka probably damage the data as well)-Load the source data into a data-warehouse\/mart\/lake just to make it \u2018easier\u2019 to access.<\/span><\/li>\r\n
    • Realizing the required analytical results are not in the data-warehouse\/mart\/lake, extract some data into Excel\/PowerBI\/BI-tool-of-choice where you can write your analysis calculations, aggregations, etc.<\/span><\/li>\r\n
    • Report analysis results, but forget to or cannot put the analysis results back into the data-warehouse\/mart\/lake.<\/span><\/li>\r\n
    • Repeat the same process every time there is a similar (or identical) analysis required.<\/span><\/li>\r\n
    • \u2026 don\u2019t relax, another analysis request shortly follows \ud83d\ude41<\/span><\/li>\r\n<\/ul>\r\n

      IntelligentGraph Benefits<\/span><\/h1>\r\n

      IntelligentGraph moves analysis into the knowledge graph rather than moving data to the analysis engine, avoiding the groundhog-analysis-way:<\/span><\/p>\r\n

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      • Improves analyst performance and efficiency<\/span>\r\n
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        • Eliminates the need for analysts to create ELT to move data to the analysis engine. <\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
        • Simplifies complex calculations and aggregations<\/span>\r\n
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          • PathQL language greatly simplifies navigating and aggregating throughout the graph.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
          • Ensures calculation and KPI concurrency<\/span>\r\n
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            • Calculations are performed in-situ with the data, so no need to re-export data to the analysis engine to view updated results.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
            • Uses familiar scripting language<\/span>\r\n
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              • Scripts expressed in any of multiple scripting languages including Python, Javascript, Groovy, and Java.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
              • Improves analysis performance and efficiency<\/span>\r\n
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                • Time-to-answer reduced or eliminated as analysis is equivalent to reporting<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
                • Ensures analysis effort is shared with all<\/span>\r\n
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                  • Analysis results become part of the graph which can be used by others ensuring consistency.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
                  • Self-documenting analysis path to raw data<\/span>\r\n
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                    • The IntelligentGraph contains calculation scripts that define which calculations will be performed on what data (or other calculation results).<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
                    • Improves analysis accuracy by providing provenance of all calculations<\/span>\r\n
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                      • Trace of any analysis through to raw data is automatically available.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
                      • Simplifies reporting<\/span>\r\n
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                        • Reporting tools can be used that focus on report appearance rather than calculation capability since the latter is performed in the IntelligentGraph. <\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
                        • Highly scalable<\/span>\r\n
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                          • IntelligentGraph is built upon the de-facto graph standard RDF4J, allowing for the use of any RDF4J compliant datastore.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
                          • Standard support<\/span>\r\n
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                            • Access to IntelligentGraph for querying, reporting, and more is unchanged from any RDF-based KnowledgeGraph.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
                            • Evolutionary, not revolutionary modeling and analysis<\/span>\r\n
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                              • Graph-based models offer the ability to evolve as data analysis needs grow, such as adding new dimensions to the data, unlike a \u2018traditional\u2019 data mart or warehouse which usually require a rebuild.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
                              • Creates the Intelligent Internet of Things<\/span>\r\n
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                                • Scripts can access external data, such as IoT, on-demand allowing IoT-based calculations and analysis to be performed in-situ.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n
                                • Eliminates spreadsheet-hell<\/span>\r\n
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                                  • All spreadsheet calculations and aggregations can be moved into the graph, leaving the spreadsheet as a presentation tool. This eliminates the problem of undocumented calculations and inconsistent calculations in different spreadsheets.<\/span><\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n\r\n
                                    <\/figure>\r\n","protected":false},"excerpt":{"rendered":"

                                    Data is rather like poor red wine: it neither travels nor ages well. IntelligentGraph avoids data traveling by moving analysis into the knowledge graph rather than moving data to the analytics engine, obsoleting the groundhog-analysis-way<\/p>\n","protected":false},"author":1,"featured_media":3666,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"bgseo_title":"","bgseo_description":"","bgseo_robots_index":"index","bgseo_robots_follow":"follow","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0},"categories":[50],"tags":[59,41,40,35,55,57,34,58],"_links":{"self":[{"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/posts\/3620"}],"collection":[{"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/comments?post=3620"}],"version-history":[{"count":10,"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/posts\/3620\/revisions"}],"predecessor-version":[{"id":3667,"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/posts\/3620\/revisions\/3667"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/media\/3666"}],"wp:attachment":[{"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/media?parent=3620"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/categories?post=3620"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/inova8.com\/bg_inova8.com\/wp-json\/wp\/v2\/tags?post=3620"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}