{"course":{"productid":35211,"modality":1,"active":true,"language":"fr","title":"Exploring and Analyzing Data with Splunk","productcode":"EADS","vendorcode":"SP","vendorname":"Splunk","fullproductcode":"SP-EADS","courseware":{"has_ekit":false,"has_printkit":true,"language":""},"url":"https:\/\/portal.flane.ch\/course\/splunk-eads","objective":"<ul>\n<li>Analytics Framework<\/li><li>Exploring and visualizing data<\/li><li>Cleaning and Preprocessing Data<\/li><li>Numerical and String based clustering<\/li><li>Data Correlation<\/li><li>Meta Transactions<\/li><li>Detecting Anomalies<\/li><li>Forecasting<\/li><\/ul>","essentials":"<p>To be successful, students should have a solid understanding of the following courses:\n<\/p>\n<ul>\n<li>Intro to Splunk<\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/splunk-suf\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Using Fields <span class=\"fl-prod-pcode\">(SUF)<\/span><\/a><\/span><\/li><li>Scheduling Reports and Alerts<\/li><li>Visualizations<\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/splunk-wwt\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Working with Time <span class=\"fl-prod-pcode\">(WWT)<\/span><\/a><\/span><\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/splunk-ssp\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Statistical Processing <span class=\"fl-prod-pcode\">(SSP)<\/span><\/a><\/span><\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/splunk-scv\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Comparing Values <span class=\"fl-prod-pcode\">(SCV)<\/span><\/a><\/span><\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/splunk-srm\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Result Modification <span class=\"fl-prod-pcode\">(SRM)<\/span><\/a><\/span><\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/splunk-lls\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Leveraging Lookups and Subsearches <span class=\"fl-prod-pcode\">(LLS)<\/span><\/a><\/span><\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/splunk-sclas\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Correlation Analysis <span class=\"fl-prod-pcode\">(SCLAS)<\/span><\/a><\/span><\/li><li>Search Under the Hood<\/li><li>Intro to Knowledge Objects<\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/splunk-cfe\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Creating Field Extractions <span class=\"fl-prod-pcode\">(CFE)<\/span><\/a><\/span><\/li><li><span class=\"cms-link-marked\"><a class=\"fl-href-prod\" href=\"\/swisscom\/fr\/course\/splunk-sso\"><svg role=\"img\" aria-hidden=\"true\" focusable=\"false\" data-nosnippet class=\"cms-linkmark\"><use xlink:href=\"\/css\/img\/icnset-linkmarks.svg#linkmark\"><\/use><\/svg>Search Optimization <span class=\"fl-prod-pcode\">(SSO)<\/span><\/a><\/span><\/li><\/ul>","outline":"<h4>Topic 1 &ndash; What is Data Science<\/h4><ul>\n<li>Define terms related to analytics and data science<\/li><li>Describe the analytics workflow<\/li><li>Describe Artificial Intelligence and Machine Learning<\/li><li>Examine common Machine Learning myths<\/li><li>Describe Splunk&rsquo;s Machine Learning tools<\/li><\/ul><h4>Topic 2 &ndash; Exploratory Data Analysis<\/h4><ul>\n<li>Use bin and makecontinuous to restructure and visualize data<\/li><li>Examine field statistics with fieldsummary<\/li><li>Transform fields with eval and fillnull<\/li><li>Clean text with the rex and cleantext commands<\/li><li>Solve Anscombe&rsquo;s Quartet<\/li><li>Apply boxplots and 3d scatterplots to visualize data<\/li><\/ul><h4>Topic 3 &ndash; Event Clustering<\/h4><ul>\n<li>Take a behavioral based approach to cluster data<\/li><li>Cluster numerical fields using the kmeans command<\/li><li>Cluster based of string similarity with the cluster command<\/li><li>Find patterns in clusters<\/li><\/ul><h4>Topic 4&ndash; Correlations and Transactions<\/h4><ul>\n<li>Define correlation and co-occurrence<\/li><li>Use SPL correlation commands<\/li><li>Use the statistical tests from the Machine Learning Toolkit to correlate fields<\/li><li>Use streamstats and chart commands to correlate data<\/li><\/ul><h4>Topic 5&ndash; Anomaly Detection<\/h4><ul>\n<li>Define Statistical Outliers<\/li><li>Use Add-hoc methods of numerical anomaly detection<\/li><li>Find numerical or categorical anomalies with the AnomalyDetection command<\/li><\/ul><h4>Topic 6 &ndash; Forecasting<\/h4><ul>\n<li>Define forecasting use cases<\/li><li>Use the predict command to forecast future timeseries<\/li><\/ul>","summary":"<p>This 9-hour course is for users who want to attain operational intelligence level 4, (business insights) and covers exploratory data analysis by using statistical tools and custom visualizations.<\/p>","objective_plain":"- Analytics Framework\n- Exploring and visualizing data\n- Cleaning and Preprocessing Data\n- Numerical and String based clustering\n- Data Correlation\n- Meta Transactions\n- Detecting Anomalies\n- Forecasting","essentials_plain":"To be successful, students should have a solid understanding of the following courses:\n\n\n\n- Intro to Splunk\n- Using Fields (SUF)\n- Scheduling Reports and Alerts\n- Visualizations\n- Working with Time (WWT)\n- Statistical Processing (SSP)\n- Comparing Values (SCV)\n- Result Modification (SRM)\n- Leveraging Lookups and Subsearches (LLS)\n- Correlation Analysis (SCLAS)\n- Search Under the Hood\n- Intro to Knowledge Objects\n- Creating Field Extractions (CFE)\n- Search Optimization (SSO)","outline_plain":"Topic 1 \u2013 What is Data Science\n\n\n- Define terms related to analytics and data science\n- Describe the analytics workflow\n- Describe Artificial Intelligence and Machine Learning\n- Examine common Machine Learning myths\n- Describe Splunk\u2019s Machine Learning tools\nTopic 2 \u2013 Exploratory Data Analysis\n\n\n- Use bin and makecontinuous to restructure and visualize data\n- Examine field statistics with fieldsummary\n- Transform fields with eval and fillnull\n- Clean text with the rex and cleantext commands\n- Solve Anscombe\u2019s Quartet\n- Apply boxplots and 3d scatterplots to visualize data\nTopic 3 \u2013 Event Clustering\n\n\n- Take a behavioral based approach to cluster data\n- Cluster numerical fields using the kmeans command\n- Cluster based of string similarity with the cluster command\n- Find patterns in clusters\nTopic 4\u2013 Correlations and Transactions\n\n\n- Define correlation and co-occurrence\n- Use SPL correlation commands\n- Use the statistical tests from the Machine Learning Toolkit to correlate fields\n- Use streamstats and chart commands to correlate data\nTopic 5\u2013 Anomaly Detection\n\n\n- Define Statistical Outliers\n- Use Add-hoc methods of numerical anomaly detection\n- Find numerical or categorical anomalies with the AnomalyDetection command\nTopic 6 \u2013 Forecasting\n\n\n- Define forecasting use cases\n- Use the predict command to forecast future timeseries","summary_plain":"This 9-hour course is for users who want to attain operational intelligence level 4, (business insights) and covers exploratory data analysis by using statistical tools and custom visualizations.","skill_level":"Intermediate","version":"1.0","duration":{"unit":"d","value":0,"formatted":"9 heures"},"pricelist":{"List Price":{"US":{"country":"US","currency":"USD","taxrate":null,"price":1000},"GB":{"country":"GB","currency":"GBP","taxrate":20,"price":835},"PL":{"country":"PL","currency":"USD","taxrate":23,"price":1000},"DE":{"country":"DE","currency":"EUR","taxrate":19,"price":1000},"NL":{"country":"NL","currency":"EUR","taxrate":21,"price":1000},"CA":{"country":"CA","currency":"CAD","taxrate":null,"price":1380},"CH":{"country":"CH","currency":"CHF","taxrate":8.1,"price":1100}}},"lastchanged":"2026-03-26T00:56:29+01:00","parenturl":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-courses","nexturl_course_schedule":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course-schedule\/35211","source_lang":"fr","source":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course\/splunk-eads"}}