[Docs] Remove first person "I" from getting started (#27155)
Avoid first person style and consistently switch to an unpersonal style in the getting started docs.
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@ -13,7 +13,7 @@ Here are a few sample use-cases that Elasticsearch could be used for:
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* You run a price alerting platform which allows price-savvy customers to specify a rule like "I am interested in buying a specific electronic gadget and I want to be notified if the price of gadget falls below $X from any vendor within the next month". In this case you can scrape vendor prices, push them into Elasticsearch and use its reverse-search (Percolator) capability to match price movements against customer queries and eventually push the alerts out to the customer once matches are found.
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* You run a price alerting platform which allows price-savvy customers to specify a rule like "I am interested in buying a specific electronic gadget and I want to be notified if the price of gadget falls below $X from any vendor within the next month". In this case you can scrape vendor prices, push them into Elasticsearch and use its reverse-search (Percolator) capability to match price movements against customer queries and eventually push the alerts out to the customer once matches are found.
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* You have analytics/business-intelligence needs and want to quickly investigate, analyze, visualize, and ask ad-hoc questions on a lot of data (think millions or billions of records). In this case, you can use Elasticsearch to store your data and then use Kibana (part of the Elasticsearch/Logstash/Kibana stack) to build custom dashboards that can visualize aspects of your data that are important to you. Additionally, you can use the Elasticsearch aggregations functionality to perform complex business intelligence queries against your data.
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* You have analytics/business-intelligence needs and want to quickly investigate, analyze, visualize, and ask ad-hoc questions on a lot of data (think millions or billions of records). In this case, you can use Elasticsearch to store your data and then use Kibana (part of the Elasticsearch/Logstash/Kibana stack) to build custom dashboards that can visualize aspects of your data that are important to you. Additionally, you can use the Elasticsearch aggregations functionality to perform complex business intelligence queries against your data.
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For the rest of this tutorial, I will guide you through the process of getting Elasticsearch up and running, taking a peek inside it, and performing basic operations like indexing, searching, and modifying your data. At the end of this tutorial, you should have a good idea of what Elasticsearch is, how it works, and hopefully be inspired to see how you can use it to either build sophisticated search applications or to mine intelligence from your data.
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For the rest of this tutorial, you will be guided through the process of getting Elasticsearch up and running, taking a peek inside it, and performing basic operations like indexing, searching, and modifying your data. At the end of this tutorial, you should have a good idea of what Elasticsearch is, how it works, and hopefully be inspired to see how you can use it to either build sophisticated search applications or to mine intelligence from your data.
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== Basic Concepts
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== Basic Concepts
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@ -660,7 +660,7 @@ Now that we've gotten a glimpse of the basics, let's try to work on a more reali
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--------------------------------------------------
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--------------------------------------------------
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// NOTCONSOLE
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// NOTCONSOLE
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For the curious, I generated this data from http://www.json-generator.com/[`www.json-generator.com/`] so please ignore the actual values and semantics of the data as these are all randomly generated.
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For the curious, this data was generated using http://www.json-generator.com/[`www.json-generator.com/`], so please ignore the actual values and semantics of the data as these are all randomly generated.
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[float]
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[float]
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=== Loading the Sample Dataset
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=== Loading the Sample Dataset
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@ -1284,4 +1284,4 @@ There are many other aggregations capabilities that we won't go into detail here
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== Conclusion
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== Conclusion
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Elasticsearch is both a simple and complex product. We've so far learned the basics of what it is, how to look inside of it, and how to work with it using some of the REST APIs. I hope that this tutorial has given you a better understanding of what Elasticsearch is and more importantly, inspired you to further experiment with the rest of its great features!
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Elasticsearch is both a simple and complex product. We've so far learned the basics of what it is, how to look inside of it, and how to work with it using some of the REST APIs. Hopefully this tutorial has given you a better understanding of what Elasticsearch is and more importantly, inspired you to further experiment with the rest of its great features!
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