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{"sheet":"IoTSiteWiseCalculator","index":0,"n_rows":70,"n_cols":14,"rows_kept":70,"cut":false,"hidden":false,"merged":[[29,0,29,2],[29,5,29,8],[36,0,36,2],[36,5,36,8],[33,13,33,18],[35,13,35,18],[37,13,37,18],[41,13,63,16],[32,0,32,2],[32,5,32,8],[38,0,38,2],[38,5,38,8],[40,0,40,2],[40,5,40,8],[1,13,1,18],[0,0,0,18],[11,0,11,18],[12,0,12,18],[6,3,6,8],[7,13,7,16],[2,13,5,16],[8,13,10,18],[14,13,14,18],[43,0,43,2],[16,5,27,8],[16,3,17,3],[13,13,13,18],[15,0,15,2],[40,13,40,16],[16,13,29,18],[32,13,32,16],[36,13,36,16],[38,13,38,16],[39,13,39,18],[34,13,34,18],[31,13,31,18],[30,13,30,18],[15,13,15,18]]}
["AWS IoT SiteWise Pricing Calculator Tool\nThis tool provide an estimate of charges for AWS IoT SiteWise based on information provided. Monthly charges will be based on actual usage of the service."]
["Customer Inputs","Unit","Value",null,null,"GB of raw GB of  telemetry data","Unit","Value","Derived measurements/day","TQVs/Message",null,null,null,"Notes and Instructions"]
["Number of measurments","count/day",null,"OR",null,"Raw telemetry data in GB","GB/day",null,{"$f":"H3*(1024^3)/8","v":0}]
["Number of tags","count/global",null,"AND",null,"Average TQVs/tag/min","TQVPM",null,{"$f":"I3/24/60/C4","v":{"$error":"#DIV/0!"}}]
["Monitor Users Count","unique active users"]
["Cloud data availability ","seconds",10]
["Use of SW Gateway","Yes/No","Yes"]
["Data Processing Pack at the edge","active gateways/month",null,null,null,null,null,null,null,null,null,null,null,"You can use SiteWise data processing pack to process and route your data locally. you can choose to send only aggregated data to the cloud. Use this feature to optimize your bandwidth usage and reduce ingestion costs."]
["Buffered Ingestion (% of data that can be batched)","%",0.8,null,null,null,null,null,null,null,null,null,null,"Percentage of data with  user-defined latency tolernace vs data needed for near real-time.\n80% at 5 minutes means that 80% of data has latency tolerance of 5 minutes or more. \nNote: background color of cell C9 turns red when buffered ingestion does not improve ingestion cost."]
["Buffered - Wait Time ( in minutes)","minutes",5]
["Region",null,"US East (N. Virginia)"]
["Additional Options for a detailed, more granular estimate. \nNote: Leave the following blank if more detailed pricing is not required or data points are not available"]
["Note: Edge data processing, filtering, and deadbanding can reduce the volume of real-time data that is transferred to the cloud. \nA deadband specifies a window of expected fluctuations in the incoming data values from your OPC-UA source. If the values fall within this window, your OPC-UA server won't send it to the AWS Cloud. Deadbanding and filtering may be supported by your OPC-UA server."]
["Deadbandable Data Volume (Hot)","%",0,null,null,null,null,null,null,null,null,null,null,"We assume the total number of daily measurements (C3) is the volume of data that is transmitted to the cloud."]
["Average time-series measurement size","bytes",81,null,null,null,null,null,null,null,null,null,null,"Average size of each time-series measurement including overhead. Each double is 8 bytes, however asset id, property alias, timestamp, quality, etc. add overhead. Default assumed value based on historical inputs is 81 bytes (8 bytes + 73 overhead)"]
["2. Real-time data Ingestion breakdown: real time data can be grouped in different categories and cohorts. More grandular ingestion pricing can be provided based on these ingestion groups. \nData needed for this breakdown is 1/real time data volume % 2/volume of tags 3/acceptable latency tolerance of each group",null,null,null,null,null,null,null,null,null,null,null,null,"For more granular pricing fill in this section, Otherwise, leave blank.\nIn this granular calculation, you can group your real-time data into buckets with varying latency requirement and get a more accurate cost breakdown. \nfor example if 10% of my real-time data is represented by 30 tags and is needed in 1 second. you can put 10% for C12, 30 for C13 and 1 for C14, etc. Sum of percentages should equal 100%"]
["real time data volume (Group 1)","% ",null,{"$f":"IF($C$17+$C$20+$C$23+$C26<>1, \"Sum of real time data volume does not add up to 100%\", TRUE)","v":"Sum of real time data volume does not add up to 100%"},null,null,null,null,null,null,null,0.5,null,{"$f":"IF($C$17+$C$20+$C$23+$C26<>1, \"Sum of real time data volume does not add up to 100%\", TRUE)","v":"Sum of real time data volume does not add up to 100%"}]
["Volume of tags (Group 1)","count",null,null,null,null,null,null,null,null,null,40]
["latency tolerance (Group 1)","seconds",null,{"$f":"IF(D17=TRUE,IF(ISBLANK($C$19),\"Latency tolerance is missing\",TRUE))","v":false},null,null,null,null,null,{"$f":"IF(AND($D$19=TRUE, $C$19<>\"\"), IF($C$3*(1-$C$9)*(1-$C$14)*$C$17/$C$18/(24*3600/$C$19)<1, 1, IF($C$3*(1-$C$9)*(1-$C$14)*$C$17/$C$18/(24*3600/$C$19)>10, 10, $C$3*(1-$C$9)*(1-$C$14)*$C$17/$C$18/(24*3600/$C$19))), \"NA\")","v":"NA"},null,1]
["real time data volume(Group 2)","%",null,null,null,null,null,null,null,null,null,0.3]
["Volume of tags (Group 2)","count",null,null,null,null,null,null,null,null,null,100]
["latency tolerance (Group 2)","seconds",null,{"$f":"IF(C20<>\"\",IF(ISBLANK(C22),\"latency tolerance is missing\",TRUE),TRUE)","v":true},null,null,null,null,null,{"$f":"IF(AND($D$22=TRUE, $C$22<>\"\"),IF($C$3*(1-$C$9)*(1-$C$14)*$C$20/$C$21/(24*3600/$C$22)<1, 1, IF($C$3*(1-$C$9)*(1-$C$14)*$C$20/$C$21/(24*3600/$C$22)>10, 10, $C$3*(1-$C$9)*(1-$C$14)*$C$20/$C$21/(24*3600/$C$22))), \"NA\")","v":"NA"},null,10]
["real time data volume(Group 3)","%",null,null,null,null,null,null,null,null,null,0.2]
["Volume of tags (Group 3)","count",null,null,null,null,null,null,null,null,null,10]
["latency tolerance (Group 3)","seconds",null,{"$f":"IF($C$23<>\"\",IF(ISBLANK($C$25),\"latency tolerance is missing\",TRUE),TRUE)","v":true},null,null,null,null,null,{"$f":"IF(AND($D$25=TRUE, $C$25<>\"\"), IF($C$3*(1-$C$9)*(1-$C$14)*$C$23/$C$24/(24*3600/$C$25)<1, 1, IF($C$3*(1-$C$9)*(1-$C$14)*$C$23/$C$24/(24*3600/$C$25)>10, 10, $C$3*(1-$C$9)*(1-$C$14)*$C$23/$C$24/(24*3600/$C$25))),\"NA\")","v":"NA"},null,30]
["real time data volume(Group 4)","%"]
["Volume of tags (Group 4)","count"]
["latency tolerance (Group 4)","seconds",null,{"$f":"IF($C$26<>\"\",IF(ISBLANK($C$28),\"latency tolerance is missing\",TRUE),TRUE)","v":true},null,null,null,null,null,{"$f":"IF(AND($D$28=TRUE, $C$28<>\"\"), IF($C$3*(1-$C$9)*(1-$C$14)*$C$26/$C$27/(24*3600/$C$28)<1, 1, IF($C$3*(1-$C$9)*(1-$C$14)*$C$26/$C$27/(24*3600/$C$28)>10, 10, $C$3*(1-$C$9)*(1-$C$14)*$C$26/$C$27/(24*3600/$C$28))),\"NA\")","v":"NA"}]
["average hot data frequency","count/tag/minute",null,null,null,"Average TQVs/tag/publish",null,{"$f":"IF(IF($C$6>10, MAX(C3,I3)/C4/24/(3600/C6), IF(MAX(C3,I3)/$C$4/24/(3600/C6)<1,1, (IF(MAX(C3,I3)/$C$4/24/(3600/C6)>10, 10, MAX(C3,I3)/$C$4/24/(3600/C6)))))>10, 10, IF(C6>10, MAX(C3,I3)/$C$4/24/(3600/C6), IF(MAX(C3,I3)/$C$4/24/(3600/C6)<1,1, (IF(MAX(C3,I3)/$C$4/24/(3600/C6)>10, 10, MAX(C3,I3)/$C$4/24/(3600/C6))))))","v":{"$error":"#DIV/0!"}}]
["3. Number of daily Metrics/Transforms: Enter the total number real-time metrics and transforms or on-demand computations that are performed daily. Please leave blank if unsure"]
["Total Computations (Metrics/transforms/On-Demand)","Daily Count",null,null,null,null,null,null,null,null,null,null,null,"Total Number of daily metrics, transforms, and computations "]
["Total Number of unique metrics and transforms","Monthly",null,null,null,null,null,null,null,null,null,null,null,"Total number of unique metrics and transforms (leave empty if not sure)"]
["4. Daily Volume of retrieval: please enter the total volume of daily messages or GB scanned for retreival. Each API call can return multiple messages. See instructions for each row"]
["Daily Egress Messages for operational workloads \n(hot tier)","Daily Count",null,null,null,null,null,null,null,null,null,null,null,"Number of daily messages in response to egress API calls from the hot tier for operational workloads measured in 4KB or 50 property values per increment"]
["Daily Egress Messages for analytical workloads \n(warm tier)","Daily Count",null,null,null,null,null,null,null,null,null,null,null,"Number of daily messages in response to egress API calls measured in 20 KB increments with a minimum of 10 messages per response from a single data stream from the warm storage tier for analytical workloads "]
["SQL","GB scanned/day",null,null,null,null,null,null,null,null,null,null,null,"Volume of data scanned for SQL retreival in GB scanned per day, metered in 100KB increments.\nFor example, if you scan 1GB of data in a day and each SQL request scans 50KB, You have 20K requests in one day. Each request is measured in 100 KB increments, amounting to 2GB of data scanned. \nThe volume of data scanned per day will be calculated as 2GB (20K requests of 100 KB) of data scanned per day.\nNote: Data retreival fees are charged separately "]
["5. Data retention: Please enter the volume of data that will be stored in SiteWise Warm tier on a monthly basis. Please leave blank if unsure"]
["Warm Tier Storage ","GB/month",null,null,null,null,null,null,null,null,null,null,null,"long term storage of time-series data, priced for long term storage "]
["6. cold tier export: Yes for 6-hour export to the customer-managed cold tier. Please leave as No if unsure"]
["Enable 6-hour Export?","Yes/No","No",null,null,null,null,null,null,null,null,null,null,"Customers may want to export data to the customer-owned S3 bucket. S3 costs are calculated separately. \nNote: If you're enabling warm tier, this may not be required since warm tier stores time-series data at near S3 costs and provides performant retreival characteristics.\n"]
["7. One-time historical data import : Storage in SiteWise managed warm storage",null,null,null,null,null,null,null,null,null,null,null,null,"Please review instructions and Examples in the reference document"]
["Enter volume of historical measurements that are to be imported into service-managed warm tier","GB"]
[]
[]
["Storage (measurements)","GB/month",{"$f":"(MAX(C3,I3)*(1-C14)+C31)*30*(C15)/(1024^3)","v":0}]
["Storage (auto-aggregates)","GB/month",{"$f":"(C4+C32)*(1+24+96+IF(H29>=1,1440,1440*H29))*30*120/1024^3","v":{"$error":"#DIV/0!"}}]
["Storage (total)","GB/month",{"$f":"C45+C46","v":{"$error":"#DIV/0!"}}]
["Storage Price (Hot Tier)","$/Month",{"$f":"$C$47*VLOOKUP($C$11,Reference_Pricing!$A$3:$D$12,4,FALSE)","v":{"$error":"#DIV/0!"}}]
["Storage (warm)","$/Month",{"$f":"$C$38*VLOOKUP($C$11,Reference_Pricing!$A$3:$E$12,5,FALSE)","v":0}]
["Messaging Price (Hot tier)","$/Month",{"$f":"IF(AND($D$28,$D$25,$D$22,$D$19,$D$17)=TRUE,$C$3*(1-$C$9)*(1-$C$14)*$C$17/$J$19+IF($J22<>\"NA\",($C$3*(1-$C$9)*(1-$C$14)*$C$20)/$J$22,0)+IF($J$25<>\"NA\",($C$3*(1-$C$9)*(1-$C$14)*$C$23)/$J$25,0)+IF($J28<>\"NA\",$C$3*(1-$C$9)*(1-$C$14)*$C$26/$J$28,0),IF(ISBLANK($C$17),(MAX($C$3,$I$3)*(1-$C$9)*(1-$C$14)+$C$31)/IF(UPPER($C$7)=\"YES\",$H$29,1)))*VLOOKUP($C$11,Reference_Pricing!$A$3:$D$12,2,FALSE)*30/1000000","v":{"$error":"#DIV/0!"}}]
["Messaging Price (buffered)","$/Month",{"$f":"IF(AND($C$9>0, $C$3*$C$9/24/(60/$C$10)*C15/(1024)/5<2000), 2000, $C$3*$C$9/24/(60/$C$10)*C15/(1024)/5)*24*(60/$C$10)*30*VLOOKUP($C$11,Reference_Pricing!$A$3:$D$12,2,FALSE)/1000000","v":17.28}]
["PCA (Hot tier)","$/Month",{"$f":"C50/2","v":{"$error":"#DIV/0!"}}]
["PCA (buffered Tier)","$/Month","FREE"]
["SW Edge DPP","$/Month",{"$f":"VLOOKUP(C11,Reference_Pricing!A2:J13,10,FALSE)*C8","v":0}]
["Monitor Price","$/Month",{"$f":"VLOOKUP(C11,Reference_Pricing!A2:J13,9,FALSE)*C5","v":0}]
["Export Price ","$/Month",{"$f":"IF(UPPER(C40)=\"YES\", MAX(C4,I4)*4*VLOOKUP(C11, Reference_Pricing!A2:H13,8, FALSE)/1000*30,0)","v":0}]
["Computation Cost","$/Month",{"$f":"$C$31*30*VLOOKUP(IoTSiteWiseCalculator!$C$11,Reference_Pricing!A:E,3,FALSE)/1000000","v":0}]
["Retreival Cost","$/Month",{"$f":"$C$34*30*VLOOKUP($C$11,Reference_Pricing!$A$3:$E$12,2,FALSE)/1000000+$C$35*30*VLOOKUP($C$11,Reference_Pricing!A3:E13,2,FALSE)/1000000","v":0}]
["SQL Cost","$/Month",{"$f":"$C$36*30*VLOOKUP($C$11,Reference_Pricing!A3:G13,7,FALSE)","v":0}]
["Total","$/Month",{"$f":"SUM(C48:C59)","v":{"$error":"#DIV/0!"}}]
["One-time Historical Data import Cost"]
["Storage Cost",null,{"$f":"$C$42*VLOOKUP($C$11,Reference_Pricing!$A$3:$E$12,5,FALSE)","v":0}]
["Ingestion Cost (Messaging)",null,{"$f":"$C$42*1024^2/5*VLOOKUP($C$11,Reference_Pricing!$A$3:$D$12,2,FALSE)/1000000","v":0}]
["Total",null,{"$f":"SUM(C62:C63)","v":0}]
[]
[]
[]
[]
[]
[null,null," "]

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[]
["Regions Pricing","messaging","processing","storage","warm storage","Regions Pricing","SQL","Export","Monitor","Edge Processing"]
["US East (N. Virginia)",1,0.5,0.3,0.03,"Yes",0.2,5.0000000000000001E-3,10,200]
["US West (Oregon)",1,0.5,0.3,0.03,"No",0.2,5.0000000000000001E-3,10,200,{"$f":"G4/$G$3","v":1}]
["Asia Pacific (Mumbai)",1.3,0.65,0.39,3.9E-2,null,0.26,6.5000000000000006E-3,10,200,{"$f":"G5/$G$3","v":1.3}]
["Asia Pacific (Seoul)",1.3,0.65,0.39,3.9E-2,null,0.26,6.5000000000000006E-3,10,200,1.3]
["Asia Pacific (Singapore)",1.3,0.65,0.39,3.9E-2,null,0.26,6.5000000000000006E-3,10,200,1.3]
["Asia Pacific (Sydney)",1.2,0.6,0.36,3.5999999999999997E-2,null,0.24,6.0000000000000001E-3,10,200,1.2]
["Asia Pacific (Tokyo)",1.3,0.65,0.39,3.9E-2,null,0.26,6.5000000000000006E-3,10,200,1.3]
["Europe (Frankfurt)",1.2,0.6,0.36,3.5999999999999997E-2,null,0.24,6.0000000000000001E-3,10,200,1.2]
["Europe (Ireland)",1.2,0.6,0.36,3.5999999999999997E-2,null,0.24,6.0000000000000001E-3,10,200,1.2]
["AWS GovCloud (US-West)",1.2,0.6,0.36,3.5999999999999997E-2,null,0.24,6.0000000000000001E-3,10,200,1.2]
["China (Beijing)",9.19,4.5999999999999996,27.27,2.7549999999999999,null,1.9,4.2444999999999997E-2,70.66,1306]