Tools In The Alteryx Designer

Tools in the Alteryx DesignerThese tools were new in 8.58.69.09.19.5This list of tools is grouped by their categories on the Alteryx Designer tool palette.Group data into sets (tiles) based on valueranges in a field.Creating logical groups of your data. User definedbreaks or statistical breaks. Very good for bucketinghigh valued customers vs. low valued customersUniqueSeparate data into two streams, duplicate andunique records, based on the fields of theuser's choosing.Only want to mail to one individual, and based on aunique identifier(customer id)AppendFieldAppend the fields from a source input to everyrecord of a target input. Each record of thetarget input will be duplicated for every recordin the source input.TileJoinIconToolExampleAdding small value to a million records. A small tobig merge- Adding time stamps as well as the nameof the users who last accessed it onto your databaserecords.Search for data in one field from one datastream and replace it with a specified fieldfrom a different stream. Similar to an ExcelVLOOKUP.Think of this like Excel- find and replace. Looking forsomething and then replacing.JoinCombine two data streams based on commonfields (or record position). In the joined output,each row will contain the data from bothinputs.For instance this can be used to join Customer profiledata as well as transactional data, and join the twodata sources based on a unique customer IDJoinMultipleCombine two or more inputs based on commonfields (or record position). In the joined output,each row will contain the data from bothinputs.For instance this can be used to join Customer profiledata as well as transactional data, and join two ormore data sources based on a unique customer IDThe Make Group tool takes data relationshipsand assembles the data into groups based onthose relationships.Used primarily with Fuzzy Matching- ID 1 can match10 different values from source 2 and that becomes agroup.Identify non-identical duplicates in a datastream.Helps determine similarities in your data. Forinstance if you have 2 different data sets withdifferent ID, looking a names and address as a wayto standard and matching them up based on thesetypes of characteristics- and displays all of the id’sthat matchMatching a business listing file to Dun and Bradstreet.FindReplaceMakeGroupFuzzyMatchDun tchingUnionParseIconDescriptionToolMatch your customer or prospect file to theDun & Bradstreet business file. (requires,Alteryx with Data Package and installation ofthe Dun & Bradstreet business location file)Match your customer file to the ExperianConsumer View Household file. (requires,Alteryx with Data Package and installation ofthe Experian ConsumerView Household andindividual file)Combine two or more data streams with similarstructures based on field names or positions.In the output, each column will contain thedata from each input.Matching a customer file to Experian- example toappend segmentation values at a household levelDescriptionExampleCan be used to combine datasets with similarstructures, but with different data. You might havetransaction data stored in different files for differenttime periods, such as a sales data file for March and aseparate one for April. Assuming that they have thesame structure (the same fields), Union will join themtogether into one large file, which you can thenanalyze

Tools in the Alteryx DesignerThese tools were new in 8.58.69.09.19.5This list of tools is grouped by their categories on the Alteryx Designer tool palette.Date TimeRegExText toColumnsXML ParseTransformIconToolArrangeCountRecordsCross ansform date/time data to and from a varietyof formats, including both expression-friendlyand human readable formats.Easy conversion between strings and actual date timeformats- Example- taking Military time into standardtimes. Or turning Jan 1, 2012 into 1.1.12, etc.Parse, match, or replace data using regularexpression syntax.An example would be if someone is trying to parseunstructured text based files- Weblogs or data feedsfrom twitter, helps arrange the data for analyticalpurposes into rows and columns.Split the text from one field into separate rowsor columns.Allows you bring customer data from an excel file forinstance that contains first name and last name inone column and split them up into 2 columns so firstname is in one column and last name is in the othercolumn- this will make it easy to sort and analyzeCleaning an xml file, parse xml textRead in XML snippets and parse them intoindividual fields.DescriptionExampleCount the records passing through the datastream. A count of zero is returned if norecords pass through.Returns a count of how many records are goingthrough the toolPivot the orientation of the data stream so thatvertical fields are on the horizontal axis,summarized where specified.Think of it as a way to change your excel spreadsheetthat has a column of customer ID’s and then next toa column of revenue. This will turn these twocolumns into two rowsCalculate a cumulative sum per record in adata stream.Can take 3 columns of sales totals and summarize 3yr totals of sales by that row. ( ie yr 1 sales 10K, yr2 15K, yr 3 25K)Summarize data by grouping, summing,counting, spatial processing, stringconcatenation, and much more. The outputcontains only the results of the calculation(s).For instance if you wanted to look at a certain groupof customers of a certain age or income level, or getan idea of how many customers you have in the stateof NYPivot the orientation of the data stream so thathorizontal fields are on the vertical axis.Think of it as a way to change your excel spreadsheetthat has a row of customer ID’s and then below thata row of revenue. This will turn these two rows intotwo columnsCalculate the weighted average of a set ofvalues where some records are configured tocontribute more than others.So if you are looking at calculating average spend,this will determine and “weight” if there are certaincustomers spending levels that are contributing tothe average.Manually transpose and rearrange fields forpresentation rtingEmailCreate a chart (Area, Column, Bar, Line, Pie,etc.) for output via the Render tool.Send emails for each record with attachmentsor e-mail generated reports if desired.Used for staging data for reportsExampleCreate bar, line, pie chartsAllows you to create dynamically updated emailcontent

Tools in the Alteryx DesignerThese tools were new in 8.58.69.09.19.5This list of tools is grouped by their categories on the Alteryx Designer tool palette.Add an image for output via the Render tool.Add graphics/image that will be included in reportArrange two or more reporting snippetshorizontally or vertically for output via theRender tool.How to arrange the pieces of your reportCreate a map for output via the Render tool.Create a map for a reportMap LegendBuilderRecombine the component parts of a maplegend (created using the Map LegendSplitter) into a single legend table, aftercustomization by other tools.Takes a customized legend and reassembles it.Map LegendSplitterSplit the legend from the Report Map tool intoits component parts for customization byother tools. (Generally recombined by theMap Legend Builder.)Help customize legends by adding symbols such as or % for instance or removing redundant textArrange reporting snippets on top of oneanother for output via the Render tool.Allows you to specify how to put a map togetherexample, putting a legend inside a map – I’d suggesta different example such as overlaying a table andchart onto a mapOutput report snippets into presentationquality reports in a variety of formats,including PDF, HTML, XLSX and DOCX.Saves reports out of AlteryxAdd a footer to a report for output via theRender tool.Apply a footer to the reportAdd a header to a report for output via theRender tool.Apply a header to the reportCreate a data table for output via the Rendertool.Creates table for selected data fieldsAdd and customize text for output via theRender tool.Allows you to customize a title or other text relatedaspects to your reportDescriptionExampleAdd a web page or Windows Explorer windowto your canvas.Helps you organize URL embedded into the canvas –I suggest a different example: Display a web page forreference in the module or use it to show a shareddirectory of macrosOrganize tools into a single box which can becollapsed or disabled.Helps you organize your module.ImageLayoutReport t tainerSpatialAdd annotation or images to the modulecanvas to capture notes or explain processesfor later reference.This will allow users to document what they didduring a certain portion of the analysis, so otherusers have an understanding

Tools in the Alteryx DesignerThese tools were new in 8.58.69.09.19.5This list of tools is grouped by their categories on the Alteryx Designer tool estGeneralizeHeat MapMake GridNon OverlapDrivetimePoly-BuildPoly-SplitSmoothSpatial eate spatial points in the data stream usingnumeric coordinate fields.Finding a spatial ref to a longitude, latitudeCalculate the distance or drive time betweena point and another point, line, or polygon.Creating the drive distance or drive time to acustomer locationIdentify the closest points or polygons in onefile to the points in a second file.As a customer, find me the nearest location to visit,optimizing my driving routeSimplify a polygon or polyline object bydecreasing the number of nodes.Object processing- generating an output map of acoastal boundary and you don’t need it to be toodetailed – significantly decrease the physical size of aspatial record can increase processing timeGenerate polygons representing differentlevels of "heat" (e.g. demand) in a givenarea, based on individual records (e.g.customers)Could be used to view where there is a heavieramount of households in a certain locationCreate a grid within spatial objects in the datastream.Use it to bucket on the ground where their customersare coming from (area, etc.)Create drive time trade areas that do notoverlap for a point file.Create drive time trade areas that do not overlap, fora point fileCreate a polygon or polyline from sets ofpoints.Build a trade area- build an object of where all of mycustomers are coming from. Building a polygon to fita series of pointsSplit a polygon or polyline into its componentpolygons, lines, or points.Break a polygon into a sequential set of points.Round off sharp angles of a polygon orpolyline by adding nodes along its lines.Crisp objects rendered on a map. (coastal view moredetailed)Extract information about a spatial object,such as area, centroid, bounding rectangle,etc.Getting the Lat/Lon of a point. Maybe the areasquare miles of a cover area for Telco/wirelessCombine two data streams based on therelationship between two sets of spatialobjects to determine if the objects intersect,contain or touch one another.Finding all customers that fall within a defined tradearea, based on their geographic proximityCreate a new spatial object from thecombination or intersection of two spatialobjects.Want to remove overlap from intersecting tradeareas.Expand or contract the extents of a spatialobject (typically a polygon).Identify all of the business on a road, by placing abuffer on that road to determine who they are/wherethey are

Tools in the Alteryx DesignerThese tools were new in 8.58.69.09.19.5This list of tools is grouped by their categories on the Alteryx Designer tool palette.Trade AreaDefine radii (including non-overlapping) ordrive-time polygons around specified points.Data sContingencyTableDetermine which fields in a database have abivariate association with one another.Create a contingency table based on selectedfields, to list all combinations of the fieldvalues with frequency and percent columns.Split the data stream into two or threerandom samples with a specified percentageof records in the estimation and validationsamples. If the total is less than 100%, theremaining records fall in the holdout sample.CreateSamplesDistributedAnalysisAllows you to fit one or more distributions tothe input data and compare them based on anumber of Goodness-of-Fit* statistics. Basedon the statistical significance (p-values) of theresults of these tests, the user can determinewhich distribution best represents the data.Produce a concise summary report ofdescriptive statistics for the selected datafields.FieldSummaryReportDefining boundaries for where your customers orprospects are coming fromExampleFor example, if the user is trying to determine whoshould be contacted as part of a direct marketingcampaign, to estimate the probability a prospect willrespond favorably if contacted in the marketingcampaign.For example you can build a table of males andfemales and how many times they purchase certainproducts during a weeks’ time.For example, in the case of a direct marketingcampaign, we want to know the probability that aprospect that is contacted as part of the campaignwill respond favorably to it, before we include thatprospect on the contact list of the campaign in orderto make the decision whether to include the prospecton the list. As a result, what we really care about inselecting a predictive model to implement a businessprocess is the ability of that model to accuratelypredict new data (the model that does the best job ofpredicting data in the estimation sample does not dothe best job of predicting new data since it “over fits”the estimation sample). To do this, we need to knowthe actual outcome in order to assess modelaccuracy. As a result, we will take data where weknow the outcomes (perhaps as a result of a testimplementation of that campaign), and use part ofthe data (the estimation sample) to create a set ofcandidate predictive models, and another, separate,part of the data (the validation sample) to comparethe ability of the different candidate models to predictthe outcomes for this second set of data in order toselect the model to put into production. At times theuser may want to use a third portion of the availabledata (the holdout sample) for the purposes ofdeveloping unbiased estimates of the economicimplications of putting a model into a productionbusiness process.Helpful when trying to understand the overall natureof your data as well as make decisions about how toanalyze it. For instance, data that fits a Normaldistribution would likely be well-suited to a LinearRegression, while data that is Gamma Distributed bebetter-suited to analysis via the Gamma Regressiontool.This tool provides a concise, high level overview of allthe fields in a database. This information can beinvaluable to users in determining what fields theyneed to pay special attention to in their analysis. Forinstance, if State is a field in a customer database foran online retailer, and there is only a single customerfrom the state of Alaska, the analyst will quickly beable to determine that any analysis (ranging fromsimple means by state to more advanced predictivemodels) that involve the State field will result in veryunreliable information for Alaska. Given thisinformation, the user may decide to not use the Statefield, or to combine the Alaska customer with

Tools in the Alteryx DesignerThese tools were new in 8.58.69.09.19.5This list of tools is grouped by their categories on the Alteryx Designer tool palette.FrequencyTableHistogramReplaces the Pearson Correlation Coefficientin previous versions customers from another state (perhaps Hawaii) foranalysis purposes.For example, What is the distribution of a company’scustomers by income level? From the output, youmight learn that 35% of your customers are in highincome, 30% are in middle high, 25% are in middlelow, and 10% are in low.Provides a visual summary of the distribution ofvalues based on the frequency of intervals. Forexample, the US Census using their data on the timeoccupied by travel to work, Table 2 below shows theabsolute number of people who responded with traveltimes "at least 15 but less than 20 minutes" is higherthan the numbers for the categories above and belowit. This is likely due to people rounding their reportedjourney time.Could be used for reports to visualize contingencytables for media usage. For example, a survey ofhow important Internet reviews were in making apurchase decision (on a 1 to 10 scale), and when thecustomer searched for this information (done in timecategories from six or more from the time ofpurchase to within one hour of the point of purchase).The heat plot allows user to see that those wholooked at internet reviews five to six weeks from thepoint of purchase were most influenced by thosereviews.In many applications, the behavior of interest (e.g.,responding favorably to a promotion offer) is a fairlyrare event (untargeted or poorly targeted directmarketing campaigns often have favorable responserates that are below 2%). Building predictive modelsdirectly with this sort of rare event data is a problemsince models that predict that no one will respondfavorably to a promotion offer will be correct in thevast majority of cases. To prevent this fromhappening, it is common practice to oversample thefavorable responses so that there is a higher penaltyfor placing all customers into a non-respondercategory. This is done by taking all the favorableresponders and a sample of the non-responders toget the total percentage of favorable responders upto a user specified percentage (often 50% of thesample used to create a model).For example age and income are related. So as ageincreases so will income.The Pearson coefficient is obtained by dividingthe covariance of the two variables by theproduct of their standard deviationsTake a numeric or binary categorical(converted into a set of zero and one values)field as a response field along with acategorical field and plot the mean of theresponse field for each of the categories(levels) of the categorical field.Produce enhanced scatterplots, with optionsto include boxplots in the margins, a linearregression line, a smooth curve via nonparametric regression, a smoothed conditionalspread, outlier identification, and a regressionline. The smooth curve can expose therelationship between two variables relative toa traditional scatter plot, particularly in casesThe best use of this tool is for gaining a basicunderstanding of the nature of the relationshipbetween a categorical variable and numeric variable.For instance, it allows us to visually examine whethercustomers in different regions of the country spendmore or less on women’s apparel in a year.Shows the relationship between two numericvariables or a numeric variable and a binarycategorical variable (e.g., Yes/No). In addition to thepoints themselves, the tool also produces lines thatshow the trends in the relationships. For instance, itmay show us that household spending on restaurantmeals increases with household income, but the rateof increase slows (i.e., shows “diminishing returns”)Produce a frequency analysis for selectedfields - output includes a summary of theselected field(s) with frequency counts andpercentages for each value in a field.Provides a hi

RevoScaleR system to scale predictive analytics to millions of records) for either: (1) using the XDF file as input to a predictive analytics tool or (2) reading the file into an Alteryx data stream for further data hygiene or blending activities This can be used when building and running predictive analytics procedures on large amounts of