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`http://www.facebook.com/sharer/sharer.php?u=${pageURL}`;\r\nwindow.open(shareURL, '_blank');\r\n}\r\nif (targetClassesArr.includes('share-icon--twitter')) {\r\nconst shareURL = `https://twitter.com/intent/tweet?url=${pageURL}`;\r\nwindow.open(shareURL, '_blank');\r\n}\r\nif (targetClassesArr.includes('share-icon--email')) {\r\nconst shareURL = `mailto:?subject=Check out this news from Snowflake&body=${pageURL}`;\r\nwindow.open(shareURL);\r\n}\r\n\r\n\r\n\r\n\r\n\r\n});",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false}},":itemsOrder":["markup_editor"],":type":"snowflake-site/components/container"}},":itemsOrder":["container_949147658"],":type":"snowflake-site/components/container"},"cq:LiveSyncConfig":{"cq:isDeep":true,"cq:rolloutConfigs":[],"cq:master":"/content/experience-fragments/snowflake-site/language-masters/en/site/share-icons/share-icons",":type":"cq:LiveCopy"}},":itemsOrder":["root","cq:LiveSyncConfig"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment","appliedCssClassNames":"snowflake-responsive-component-top-padding-extra-small"}},":itemsOrder":["text","experiencefragment"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"fundamentals-main-content","appliedCssClassNames":"snowflake-responsive-container-inner-padding-large",":items":{"container_copy":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"overview","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-d98dbe65a2","additionalClasses":"headline-decoration","type":"heading2","lines":["Overview"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-c59fd336f2","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EMost people wouldn’t plan a road trip without using a GPS app or buying a map. Just imagine making a cross-country drive you’ve never made before, completely unfamiliar with possible challenging terrain or hazards, with nothing to guide you but road signs and your wits. Likewise, businesses can’t take action based on leaps of faith and guesses. Every organization needs data to guide their decisions, campaigns and business optimization — regardless of industry or size. This is where\u003Ca href=\"https://www.snowflake.com/en/product/analytics/\"\u003E data analytics\u003C/a\u003E comes in.\u003C/p\u003E\r\n\u003Cp\u003EWith data analytics, businesses uncover key intelligence they need to evolve, grow and improve for both their customers and internal teams. Without it, they’re falling behind competitors who are increasing their market share by making smart moves and careful plans backed by research.\u003C/p\u003E\r\n\u003Cp\u003EIn this guide, we’ll go over the different types of data analytics and their benefits, some typical use cases and common data analytics tools to help you start implementing data into your business decisions and analyses.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy_":{"columnClassNames":{"container_copy_copy__480869401":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__373061683":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1444615495":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__222865509":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1413360324":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy_":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__455068363":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__659376865":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1500909857":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1978652079":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"rel","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"container_copy_copy":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"what","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-61b068d1dc","additionalClasses":"headline-decoration","type":"heading2","lines":["What Is Data Analytics?"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-42d0b977cf","text":"\u003Cp\u003EData analytics is the process of examining, collecting and analyzing raw data to find patterns and draw conclusions. Data analytics fosters business growth by driving informed decision-making and helping organizations to improve performance across all teams. \u003C/p\u003E\r\n\u003Cp\u003EA variety of tools and techniques are used to gather and draw insights from data, such as spreadsheets, \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-lake-vs-data-warehouse-vs-data-mart/\"\u003Edata warehouses\u003C/a\u003E and programming languages. Any type of information can be scrutinized using those techniques — social media metrics, \u003Ca href=\"https://www.snowflake.com/en/solutions/industries/healthcare-and-life-sciences/\"\u003Epatient health history\u003C/a\u003E, inventory shrink numbers and much more. Regardless of the size of an organization or whether they have dedicated data analysts to pore over the data, any team can use common data analysis tools to uncover the information they need. A huge benefit of data analytics is that it can cut through a mass of information to reveal trends and patterns that would otherwise get lost in all the digital noise.\u003C/p\u003E\r\n\u003Cp\u003EFrom gaming companies analyzing in-game player behavior, to a \u003Ca href=\"https://www.snowflake.com/en/solutions/industries/financial-services/\"\u003Ebank\u003C/a\u003E scrutinizing customer behavior to look for potential signs of fraud, to retailers predicting when a customer is going to make their next purchase, data analytics makes it possible for businesses to create personalized experiences, mitigate risk and increase brand loyalty.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy_":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"a","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-f27d2c0cb2","additionalClasses":"headline-decoration","type":"heading2","lines":["Types of Data Analytics"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-05974e6f89","text":"\u003Cp\u003EThere are four types of data analytics, which build upon each other, moving from understanding past events to influencing future outcomes through data-backed insights and recommendations.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E1. Descriptive analytics: what happened?\u003C/h4\u003E\r\n\u003Cp\u003EThis type summarizes historical data to understand what has occurred over a period of time, such as whether there was an increase in likes on your social media posts, a higher number of in-game transactions or a decrease in quarterly product sales. Descriptive analytics is the most basic level of analysis.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E2. Diagnostic analytics: why did it happen?\u003C/h4\u003E\r\n\u003Cp\u003EThis is where things get a little more complex — and a little more interesting. Diagnostic analytics focuses on the reasons behind those past events, and involves a combination of data inputs and theorizing. Did you use the right combination of hashtags to increase the visibility of your post? Maybe the limited-time in-game event encouraged that increase in transactions?\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E3. Predictive analytics: what will happen?\u003C/h4\u003E\r\n\u003Cp\u003ENow that you understand the what and the why, you need to start planning for where you go from here. \u003Ca href=\"https://www.snowflake.com/en/fundamentals/predictive-analytics-marketing/\"\u003EPredictive analytics\u003C/a\u003E helps you figure out what’s likely to happen next. Your customer tends to buy cat litter around this time every month, so there’s a high probability they’re about to make another purchase. Your bank customer has a history of paying their bills on time, so it’s likely they’ll be reliable with their loan repayments, as well.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E4. Prescriptive analytics: what should we do?\u003C/h4\u003E\r\n\u003Cp\u003EThis is where you can start putting all of the data and information you’ve gathered and analyzed into recommendations for your next course of action. Your brand has been seeing a major month-over-month increase in sales, and your last product drop sold out within minutes of going live, so you should set up a preorder system for the next one to improve customer satisfaction.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__1444615495":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"use","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-53dfb2175a","additionalClasses":"headline-decoration","type":"heading2","lines":["Benefits of Data Analytics"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-36089489a4","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EHaving a strong data analytics strategy can have transformative effects on your business, giving your organization better visibility into what’s going well and what needs to be improved. It bridges the gap between knowing and doing, empowering your teams to optimize for efficiency and customer satisfaction. \u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E1. Informed decision-making\u003C/h4\u003E\r\n\u003Cp\u003ENo guessing, no assumptions. Make data-driven decisions based on evidence and patterns found in historical data sets for more accurate and reliable results.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E2. Improved operational efficiency\u003C/h4\u003E\r\n\u003Cp\u003EKnowing is half the battle, as they say, and data analytics provides actionable insights that can spotlight operational inefficiencies, bottlenecks and opportunities for improvement across the organization. This gives businesses the information they need to streamline processes, lower costs, enhance productivity and eliminate or refine strategies that aren’t working.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E3. Risk mitigation\u003C/h4\u003E\r\n\u003Cp\u003EAs fraud continues to evolve and increase in frequency, organizations need to remain vigilant against bad actors. Data analytics enables proactive threat and anomaly identification, making it easier for organizations to develop targeted risk-mitigation strategies with the use of AI and machine learning.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E4. Enhanced customer understanding\u003C/h4\u003E\r\n\u003Cp\u003EData analytics provides businesses with the critical customer data and insights needed to personalize customer experiences, improve their products and services, and increase customer satisfaction and loyalty. This is a huge competitive advantage that improves not just customer retention, but also new customer acquisition, and overall company growth.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__1978652079":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"benefits","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-198625db05","additionalClasses":"headline-decoration","type":"heading2","lines":["Data Analytics Steps"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-3cb7367a4a","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EWhile having a wealth of data is great, there are steps you have to take first to move it from being in a state of raw data to being able to provide you with meaningful, actionable insights. A typical data analytics project will involve working through the data analytics lifecycle: defining the objective, collecting the data, cleaning and preparing the data, and analyzing it. \u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E1. Define the objective\u003C/h4\u003E\r\n\u003Cp\u003EWhat exactly is your team hoping to glean from the data you’re collecting? What process or operation are you all trying to optimize? What campaign are you supporting? Spending time and resources gathering a mass of data isn’t helpful unless you have clear, defined goals. Outline what you’re aiming to achieve to determine data requirements and how the data should be grouped and separated.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E2. Collect the data\u003C/h4\u003E\r\n\u003Cp\u003ENow that you know exactly what you’re looking for, your data analysts can collect relevant data to support your goals. This could be anything from traffic to your site over a period of time, customer surveys, social media engagement statistics, transactional data, risk scoring and so much more.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E3. Clean and prepare the data\u003C/h4\u003E\r\n\u003Cp\u003EScrub data and examine it for errors, inconsistencies and outliers which could impact the reliability and usability of the data set. Then organize it for easy analysis. Spreadsheets are ideal for smaller data sets, but become slow and unwieldy when dealing with larger data sets. \u003Ca href=\"https://www.snowflake.com/en/fundamentals/ai-for-business-intelligence/\"\u003EBusiness intelligence\u003C/a\u003E (BI) tools are ideal for data visualization and dashboards, while \u003Ca href=\"https://www.snowflake.com/en/product/analytics/\"\u003Edatabases and data warehouses\u003C/a\u003E are necessary for very large data sets.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003E4. Analyze the data\u003C/h4\u003E\r\n\u003Cp\u003ESo you have your clean, prepped data set. Now’s the time to dive in to find patterns, relationships and trends using logic and statistical techniques. Remember the types of data analytics that we discussed earlier? This is where your data analysts utilize those methods to understand the what and why of your data and plan for next steps. \u003C/p\u003E\r\n\u003Cp\u003ESpreadsheets and free versions of BI tools are common resources for analyzing small data sets, and are typically used by smaller teams who may not even have a dedicated data analyst on staff. At the enterprise level, cloud services and big data processing frameworks and cloud services handle intermediate to very large data sets, often in conjunction with full-featured BI platforms, to produce comprehensive reporting and visualization.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__455068363":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"how","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-26ced625ae","additionalClasses":"headline-decoration","type":"heading2","lines":["Data Analytics Techniques"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-ddf8a3ad14","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EBroadly speaking, data analytics techniques are characterized into the categories of supervised and unsupervised learning. Supervised techniques learn from labeled data to make predictions, while unsupervised techniques find patterns in unlabeled data.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003ERegression analysis\u003C/h4\u003E\r\n\u003Cp\u003EThis is a supervised learning technique used to predict a continuous numerical value based on one or more independent variables. Put another way, it’s a statistical method for understanding the relationship between a dependent variable and one or more independent variables by fitting a line or curve to the data. It helps determine which variables have an impact.\u003C/p\u003E\r\n\u003Cp\u003EA key question \u003Ca href=\"https://hbr.org/2015/11/a-refresher-on-regression-analysis\"\u003Eregression analysis\u003C/a\u003E answers is, “How much or how many?” and helps businesses determine which factors matter the most and the least.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003EClassification analysis\u003C/h4\u003E\r\n\u003Cp\u003EClassification analysis answers the question, “What class or category does this belong to?” and is a powerful tool for making sense of information and making informed decisions.\u003C/p\u003E\r\n\u003Cp\u003EThis supervised learning technique is used to sort and categorize data into groups by training a classification model and then giving it new data to predict which category it belongs to. Essentially, \u003Ca href=\"https://www.indicative.com/resource/classification-analysis/\"\u003Eclassification analysis\u003C/a\u003E is all about using past, labeled data to teach a model how to categorize new, unlabeled data correctly.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003EClustering analysis\u003C/h4\u003E\r\n\u003Cp\u003EUnlike the previous two techniques, \u003Ca href=\"https://www.qualtrics.com/experience-management/research/cluster-analysis/\"\u003Eclustering analysis\u003C/a\u003E is an unsupervised learning technique used to group similar data points into clusters. There are no predefined labels or categories; the algorithm discovers the groupings within the data. Clustering analysis answers the question, “How can we group this data?”\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__222865509":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"ai","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-4a64ddc97e","additionalClasses":"headline-decoration","type":"heading2","lines":["Data Analytics Use Cases"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-ba9c1f3fe2","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EAs we mentioned at the start of this guide, every industry can benefit from data analytics, and companies of all sizes are giving themselves a competitive edge by utilizing their own data to optimize, evolve and grow. Let’s take a look at three industries — \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-analytics-for-retailers/\"\u003Eretail\u003C/a\u003E, healthcare and finance — to see how they commonly incorporate data analytics into their workflows and processes.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Ch4\u003ERetail\u003Cbr\u003E\r\n \u003C/h4\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003EAd personalization: Retailers can leverage data gathered on each customer, like purchase histories, demographics and behavioral data, to personalize the email and social media promotions they send to those customers. Creating a tailored shopping experience helps build brand loyalty and wallet share.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EOnline retail inventory management: To ensure inventory levels can meet customer demand, online retailers analyze past customer purchasing behaviors, stock levels and third-party and public data. Keeping digital shelves stocked increases customer retention and prevents them from having to click away to get what they want.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EBrick-and-mortar safety: It’s crucial that physical stores eliminate hazards that could potentially injure customers or employees. Analyzing a variety of data points, such as incident reports and safety training records, and utilizing the four types of data analytics, can help leadership develop improved employee safety training to reduce the occurrence of incidents.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch4\u003EHealthcare\u003Cbr\u003E\r\n \u003C/h4\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003EPredicting disease: Predictive analytics uses patient data, such as lifestyle, genetics and medical history, to identify patients who are at high risk of developing certain conditions. This helps doctors develop personalized treatment plans and start preventative care to get ahead of the disease.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EResource allocation: Hospitals can use data, such as seasonal emergency room admissions, to forecast patient admission levels to optimize staffing and supplies to meet patient needs, reducing wait time and increasing patient satisfaction.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EFraud detection: Data analytics can help hospitals, pharmacies and insurance companies prevent fraud by analyzing billing patterns, prescription usage and insurance claims to identify anomalies and unauthorized transactions.\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch4\u003EFinance\u003Cbr\u003E\r\n \u003C/h4\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003ERisk management: Banks can analyze a range of customer data, including spending habits, income stability and payment history to determine someone’s creditworthiness.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003ECustomer churn prediction: If certain data (like no recent banking activity or high fees) suggests that a customer may close their account, the bank can proactively offer services or incentives to retain them, like a specialized savings rate.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EAlgorithmic trading and market analysis: High-frequency trading firms use complex algorithms to analyze market data, identify market opportunities and trends, and execute trades in seconds.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__1413360324":{"columnClassNames":{"title_v2_copy":"aem-GridColumn aem-GridColumn--default--12","text_copy":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"tools","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2_copy":{"id":"title-v2-d88ef7355a","additionalClasses":"headline-decoration","type":"heading2","lines":["Common Data Analytics Tools"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text_copy":{"id":"text-6dc3f8fee2","additionalClasses":"list--blue-bullets","text":"\u003Cul\u003E\r\n\u003Cli\u003ESpreadsheets: Microsoft Excel, Google Sheets\u003C/li\u003E\r\n\u003Cli\u003EBusiness intelligence (BI) tools: Tableau, Microsoft Power BI\u003C/li\u003E\r\n\u003Cli\u003EProgramming languages: Python, R, SQL\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2_copy","text_copy"],":type":"snowflake-site/components/container"},"container_copy_copy__659376865":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"conclusion","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-539b0dfa37","additionalClasses":"headline-decoration","type":"heading2","lines":["Conclusion"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-ea2b4c898a","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EData analytics is essential to competitive advantage in virtually any industry. Data-driven decision-making creates meaningful efficiencies by optimizing internal processes, upgrading customer experience, increasing brand loyalty — and, in the case of healthcare, improving patient wellness. \u003C/p\u003E\r\n\u003Cp\u003EData continues to grow at staggering rates, increasing the complexity of analytics challenges. At the same time, tools and techniques, including advanced applications of AI, provide new ways to interact with data to draw high-value insights. Expect the evolving field of data analytics to remain an essential part of success in the digital age.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__1500909857":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","simple_snowflake_acc":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"faq","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-97e2881bb9","additionalClasses":"headline-decoration","type":"heading2","lines":["Data Analytics FAQs"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"simple_snowflake_acc":{"id":"simple-snowflake-accordion-8f26373e80","additionalClasses":"list--blue-bullets","showDivider":false,"accordionItemsList":[{"title":"What are the best courses on data analytics?","richText":"\u003Cp\u003EEveryone’s budget, learning style and career goals are different, but the best data analytics courses will provide you with a strong foundation in core skills like programming languages and data visualization tools. There are many free online courses on platforms like Coursera or DataCamp that provide an introduction to data analytics. Forbes has compiled \u003Ca href=\"https://www.forbes.com/advisor/education/certifications/best-data-analytics-certifications/\"\u003Ea list of the best online data analytics certifications\u003C/a\u003E. Snowflake offers our \u003Ca href=\"https://learn.snowflake.com/en/certifications/snowpro-advanced-dataanalyst/?pdf_name=SnowProDataAnalystStudyGuide\"\u003ESnowPro® Advanced: Data Analyst certification\u003C/a\u003E for advanced knowledge and skills used to apply comprehensive data analysis principles using Snowflake.\u003C/p\u003E\r\n"},{"title":"What tools are used for analyzing big data?","richText":"\u003Cp\u003EThere are a number of specialized tools that can handle massive volumes of data, process it quickly and extract meaningful insights. Here are a few:\u003Cbr\u003E\r\n \u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EBig data frameworks: \u003Ca href=\"https://www.snowflake.com/en/product/features/snowpark/\"\u003ESnowflake Snowpark\u003C/a\u003E, \u003Ca href=\"https://hadoop.apache.org/\"\u003EApache Hadoop\u003C/a\u003E, \u003Ca href=\"https://spark.apache.org/\"\u003EApache Spark\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003ECloud-based data warehouses: \u003Ca href=\"https://cloud.google.com/bigquery?utm_source=google&utm_medium=cpc&utm_campaign=na-US-all-en-dr-bkws-all-all-trial-e-dr-1710134&utm_content=text-ad-none-any-DEV_c-CRE_772298885512-ADGP_Hybrid+%7C+BKWS+-+EXA+%7C+Txt-Data+Analytics-Data+Analytics-BigQuery-KWID_43700082585516178-kwd-63326440124&utm_term=KW_google%20bigquery-ST_google+bigquery&gclsrc=aw.ds&gad_source=1&gad_campaignid=22970352687&gclid=Cj0KCQjwoP_FBhDFARIsANPG24P3VZl3_a-liWj18JKg9cBt96oy0h9fSeV7h9G4GzXW5-1YxrW6tdUaAsoCEALw_wcB\"\u003EGoogle BigQuery\u003C/a\u003E, \u003Ca href=\"https://aws.amazon.com/pm/redshift/?trk=a136dbb3-ff50-468b-9a66-852dc1ca985b&sc_channel=ps&ef_id=Cj0KCQjwoP_FBhDFARIsANPG24OEawaY6lV0Vnxy6v98luBjDNhrPJ71Q1KZ_r_NcuG4ZvpzRg5ZYF8aAsHOEALw_wcB:G:s&s_kwcid=AL!4422!3!651751058853!e!!g!!amazon%20redshift!19852662155!145019245577&gad_campaignid=19852662155&gbraid=0AAAAADjHtp_w47gFWrFMuAm5btwOo9ScF&gclid=Cj0KCQjwoP_FBhDFARIsANPG24OEawaY6lV0Vnxy6v98luBjDNhrPJ71Q1KZ_r_NcuG4ZvpzRg5ZYF8aAsHOEALw_wcB\"\u003EAmazon Redshift\u003C/a\u003E, \u003Ca href=\"https://www.snowflake.com/en/product/analytics/\"\u003ESnowflake\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003EBI and visualization tools: \u003Ca href=\"https://www.tableau.com/\"\u003ETableau\u003C/a\u003E, \u003Ca href=\"https://www.microsoft.com/en-us/power-platform/products/power-bi\"\u003EMicrosoft Power BI\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003EProgramming languages and libraries: \u003Ca href=\"https://www.python.org/\"\u003EPython\u003C/a\u003E, \u003Ca href=\"https://www.r-project.org/\"\u003ER\u003C/a\u003E, \u003Ca href=\"https://www.coursera.org/specializations/learn-sql-basics-data-science/paidmedia?utm_medium=sem&utm_source=gg&utm_campaign=b2c_namer_learn-sql-basics-data-science_ucdavis_ftcof_specializations_px_dr_bau_gg_sem_pr-bd_us-ca_en_m_hyb_24-12_x&campaignid=20743946861&adgroupid=154886907309&device=c&keyword=sql&matchtype=b&network=g&devicemodel=&creativeid=679514232408&assetgroupid=&targetid=kwd-10206160&extensionid=&placement=&gad_source=1&gad_campaignid=20743946861&gbraid=0AAAAADdKX6azVKefwfYb2NyuzsKTgMGOJ&gclid=Cj0KCQjwoP_FBhDFARIsANPG24PZTNLiGUpmlyl3WDAV8k-_Yop5rD7fxGmgImdMCl0YROUq1DUPB04aAsUhEALw_wcB\"\u003ESQL\u003C/a\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n"},{"title":"What is an example of data analytics?","richText":"\u003Cp\u003ECustomer segmentation in \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-analytics-for-retailers/\"\u003Eretail\u003C/a\u003E. \u003Ca href=\"https://www.snowflake.com/en/solutions/industries/retail-consumer-goods/\"\u003ERetailers\u003C/a\u003E can leverage the vast amount of customer data they collect to group customers into different segments, such as customers who only buy high-end electronics or only shop during sales. Once the segments are established, the retailer can then send targeted marketing materials to each respective segment, like tailored product recommendations or early access sales alerts.\u003C/p\u003E\r\n"},{"title":"What is the difference between data analytics and data analysis?","richText":"\u003Cp\u003EData analytics is a broad, comprehensive field with data analysis as a key part of its process. Data analysis aims to understand the past, what’s happened up to this point, to discover actionable insights and fuel data-driven decision-making. Data analytics uses data to forecast future behaviors, prescribe actions and is a forward-looking discipline. While data analysis provides descriptive insights from past data, data analytics builds on this foundation to create forward-looking strategies to take action on.\u003C/p\u003E\r\n"}],":type":"snowflake-site/components/simple-snowflake-accordion","appliedCssClassNames":"snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","simple_snowflake_acc"],":type":"snowflake-site/components/container"},"container_copy_copy__480869401":{"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","title_v2":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"customer","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-7696af51ff","additionalClasses":"headline-decoration","type":"heading2","lines":["Snowflake Customers Using Analytics"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"flexible_column_cont":{"id":"flexible-column-container-be4901e4be","type":"2-column-even","alignColumns":"match-height","containerMaxWidth":"extra-large","topPadding":"extra-small","bottomPadding":"small","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-b5b0a7ec7e","appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":items":{"card_v2":{"id":"card-v2-d300ae5d0e","configurationStatus":{"configured":true,"message":""},"title":{"id":"title","type":"heading4","lines":["VideoAmp Saves 90% in Costs and Increases Performance 10x"],":type":"snowflake-site/components/title-v2"},"button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/en/customers/all-customers/case-study/videoamp/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"Read the story"},"image":{"id":"image","lazyEnabled":true,"alt":"simon data logo","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--ef17274c-eeb9-4ffe-89f9-6319de9f005a/videoamp-customer-card%25402x.jpg?quality=85&preferwebp=true","height":"720","width":"1680",":type":"snowflake-site/components/image"},"type":"content-card",":type":"snowflake-site/components/card-v2","layoutStyle":"vertical","text":{"id":"text","text":"\u003Cp\u003EVideoAmp consolidated its data warehouse onto Snowflake to reduce complexity, save costs and deliver better products for its customers.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text"}}},":itemsOrder":["card_v2"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-47321ec658","appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":items":{"card_v2_copy":{"id":"card-v2-e22c6d15a4","configurationStatus":{"configured":true,"message":""},"title":{"id":"title","type":"heading4","lines":["Luminate Amps Entertainment Analytics with 300% Faster Data Processing and Richer Insights"],":type":"snowflake-site/components/title-v2"},"button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/customers/all-customers/case-study/luminate/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"Read the story"},"image":{"id":"image","lazyEnabled":true,"alt":"penske logo","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--1ff0d96d-96fd-4ab5-9c9b-324f2cf2b240/pfizer-card%25402x.jpg?quality=85&preferwebp=true","height":"720","width":"1680",":type":"snowflake-site/components/image"},"type":"content-card",":type":"snowflake-site/components/card-v2","layoutStyle":"vertical","text":{"id":"text","text":"\u003Cp\u003EWith Snowflake at its core, Luminate — which powers the iconic Billboard music charts and acts as the entertainment industry’s most trusted data partner — unified its data for more innovative product development and pitch-perfect data 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