VISUALISING DATAS.A N AN D@ G RAME N E R .CO M , C HIE F DATA SCIE N TIST
A DATA VISUALISATIONCHALLENGEYou will see 3 questions.You have 30 seconds.Try it!Your timerstarts now
HOW MANY NUMBERS ARE ABOVE 100? 123 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162...
HOW MANY NUMBERS ARE BELOW 10? 223 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162 ...
WHICH QUADRANT HAS HIGHEST TOTAL? 323 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 71...
The same questions again.But with a few visual cues.See how long it takes now.Your timerstarts nowA DATA VISUALISATIONCHAL...
HOW MANY NUMBERS ARE ABOVE 100? 123 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162...
HOW MANY NUMBERS ARE BELOW 10? 223 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162 ...
WHICH QUADRANT HAS HIGHEST TOTAL?23 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162...
You will be shown a set of numbersalong with a summary (average, etc)Can you make sense of the figures?WHY VISUALISE?
So is the variance in sales.Variance in price is the same.Average sales is the same too.Average price is the same.Take a l...
ARE THEY REALLY IDENTICAL? CHECK AGAIN…But in fact, the four cities aretotally different in behaviour.Boston’s sales has g...
100YEARSOFINDIA’SWEATHER19011911192119311941195119611971198119912001Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
WINNING PARTIESIn the 2004 election to LokSabha there were 1,351candidates from 6 Nationalparties, 801 candidates from36 S...
Party BJP BSP CPM INC RJD SPWINNING PARTIESIt is not often easy to seewhich party won the overallelections on a map.In the...
The CandidateTheir CasteTheir PartyWhat do people consider important when voting?Karnataka, Assembly Elections 2008
Top 1/3rdNext 1/3rdLowest 1/3rdSarvagnanagar: 35.7% out of 107941(K J George, INC)Low pollingLow pollingHosakote: 89.3% ou...
0%10%20%30%40%50%60%70%80%90%100%0 2 4 6 8 10 12 14 16 18# contestantsWinnermarginMore contestants did not reduce the winn...
0%10%20%30%40%50%60%70%80%90%100%0 2 4 6 8 10 12 14 16 18# contestantsRuner-upmarginMore contestants did reduce the runner...
CRICKETFASTEST SCORERS“I’ve always been curious… whoamong India’s prolific one-dayrun-getters had the best strikerate?Sach...
INDIAN ODI BATTING
http://gramener.com/cricket
http://gramener.com/cricket
Here are all public Indian companies, grouped by Industry. The size of thebox indicates revenue (2012) and the colour indi...
Here are all public Indian companies, grouped by Industry. The size of thebox indicates revenue (2012) and the colour indi...
68% correlationbetween AUD & EURPlot of 6 month dailyAUD - EUR valuesBlock of correlatedcurrencies… clusteredhierarchically
PRE-2009 2009 AND AFTERDecisions to increase the number oflanes on highways grew significantlypost-2009, especially as par...
AdultEducationAdminisrativeReformsAgriculturalMarketingAgricultureAnimalHusbandryCooperativeExciseFinanceFisheriesFisherie...
P.W.D.Health andfamilywelfareRevenueRuralDevelopment andPanchayatRajSocialWelfareUrbanDevelopmentWaterResourcesMinorIrriga...
VISUALISING THE MAHABHARATHA
The only other such times wereFeb 23, 2008 (28 decisions) &Dec 26, 2008 (23 decisions).Nearly two-thirds of decisionsare t...
EDUCATIONPREDICTING MARKSWhat determines a child’s marks?Do girls score better than boys?Does the choice of subject matter...
DistrictGender G BMonth Sep Nov Oct Dec Aug Feb Mar Jan Apr May Jul JunCaste OTHERS CAT-1 ST SCGovt False TrueMedium E K U...
ENGLISH05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100SOCIAL SCIENCE
05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100LANGUAGE
05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100SCIENCE
05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100MATHEMATICS
Based on the results of the 20 lakhstudents taking the Class XII examsat Tamil Nadu over the last 3years, it appears that ...
BOOKS BY EDWARD TUFTE
We handle terabyte-size data via non-traditional analytics and visualise it in real-time.Gramener visualisesyour dataGrame...
WHAT WE OFFERPLATFORM CUSTOM APPS SERVICESBuy & create yourown visualisationsusing our library ofvisual and analyticalcomp...
We handle terabyte-size data via non-traditional analytics and visualise it in real-time.Gramener visualisesyour dataGrame...
s.anand@gramener.com+91 9741 552 552
Editors Lab Delhi
Editors Lab Delhi
Editors Lab Delhi
Editors Lab Delhi
Editors Lab Delhi
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Editors Lab Delhi

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  • The earliest data visualisations were seen as far back as the mid-19th century. This is a visualisation prepared by Florence Nightingale for Queen Victoria during England’s war with France. It shows in RED the number of people that died from war wounds, in BLACK the number of people that died from other war related causes and in BLUE the number of people who died due to avoidable hospital diseases. A war is won by people and the main reason England was losing people wasn't bullets or swords but diseases. Florence Nightingale used this visualisation to request funding for hospitals, got it, and England won the war.
  • In 1854, London suffered from a Cholera epidemic. The popular theory at that time was that cholera was caused by pollution. Dr. John Snow was sceptical about this. By talking to local residents, he identified the source of the outbreak as the public water pump on Broad Street. Dr.Snow used this map to illustrate the cluster of cholera cases around the pump. He also used statistics to illustrate the connection between the quality of the water source and cholera cases. This visual was convincing enough to persuade the local council to disable the well pump by removing its handle,is regarded as the founding event of the science of epidemiology.
  • This is a map of London drawn purely using data. Every blue dot is a twitter message posted from that location. Every red dot is a photograph on Flickr taken at that location. You can see the structure of the city emerge – the roads, the river Thames, popular areas like the Tower of London, Buckingham palace, and Westminster Abbey highlighted in red, and the popular business districts highlighted in blue. This is despite not using ANY underlying map. There is nothing more here on this image, than hundreds of thousands of data points from Twitter and Flickr.
  • Who’s the best Indian one-daybatsman? The size represents every run ever scored. The colour represents speed. Red is slow, green is fast.Sehwag’s very fast – but so was Kapil, especially for his time.
  • This is a drilldown, showing every single match they played.With this, you’ll be able to see who the consistent players are, and where exactly their runs came from.You can also click to see that particular match statistics.
  • Gramener is a data analtyics and visualisation company.We have the ability to process data at a small and a large scale.We analyse the data to find non-intuitive insights that lie hidden behind it and present it as a visual story that makes those insights obvious in real time.
  • Gramener is a data analtyics and visualisation company.We have the ability to process data at a small and a large scale.We analyse the data to find non-intuitive insights that lie hidden behind it and present it as a visual story that makes those insights obvious in real time.
  • Editors Lab Delhi

    1. 1. VISUALISING DATAS.A N AN D@ G RAME N E R .CO M , C HIE F DATA SCIE N TIST
    2. 2. A DATA VISUALISATIONCHALLENGEYou will see 3 questions.You have 30 seconds.Try it!Your timerstarts now
    3. 3. HOW MANY NUMBERS ARE ABOVE 100? 123 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162 55 59 64 33 55 71 58 103 92101 56 45 34 43 15 73 78 6 9339 53 22 26 26 94 60 82 99 7411 12 36 67 70 71 97 59 73 9975 74 69 69 51 48 2 66 92 9815 10 41 58 104 94 92 84 74 8212 52 10 57 33 77 88 81 81 9115 56 25 30 21 7 66 66 78 8729 23 5 34 11 96 74 99 99 8837 10 43 15 50 71 65 60 101 9846 34 19 102 57 70 95 84 63 913 34 39 37 60 81 65 63 9 7148 46 25 50 22 64 91 76 71 79
    4. 4. HOW MANY NUMBERS ARE BELOW 10? 223 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162 55 59 64 33 55 71 58 103 92101 56 45 34 43 15 73 78 6 9339 53 22 26 26 94 60 82 99 7411 12 36 67 70 71 97 59 73 9975 74 69 69 51 48 2 66 92 9815 10 41 58 104 94 92 84 74 8212 52 10 57 33 77 88 81 81 9115 56 25 30 21 7 66 66 78 8729 23 5 34 11 96 74 99 99 8837 10 43 15 50 71 65 60 101 9846 34 19 102 57 70 95 84 63 913 34 39 37 60 81 65 63 9 7148 46 25 50 22 64 91 76 71 79
    5. 5. WHICH QUADRANT HAS HIGHEST TOTAL? 323 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162 55 59 64 33 55 71 58 103 92101 56 45 34 43 15 73 78 6 9339 53 22 26 26 94 60 82 99 7411 12 36 67 70 71 97 59 73 9975 74 69 69 51 48 2 66 92 9815 10 41 58 104 94 92 84 74 8212 52 10 57 33 77 88 81 81 9115 56 25 30 21 7 66 66 78 8729 23 5 34 11 96 74 99 99 8837 10 43 15 50 71 65 60 101 9846 34 19 102 57 70 95 84 63 913 34 39 37 60 81 65 63 9 7148 46 25 50 22 64 91 76 71 79
    6. 6. The same questions again.But with a few visual cues.See how long it takes now.Your timerstarts nowA DATA VISUALISATIONCHALLENGE
    7. 7. HOW MANY NUMBERS ARE ABOVE 100? 123 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162 55 59 64 33 55 71 58 103 92101 56 45 34 43 15 73 78 6 9339 53 22 26 26 94 60 82 99 7411 12 36 67 70 71 97 59 73 9975 74 69 69 51 48 2 66 92 9815 10 41 58 104 94 92 84 74 8212 52 10 57 33 77 88 81 81 9115 56 25 30 21 7 66 66 78 8729 23 5 34 11 96 74 99 99 8837 10 43 15 50 71 65 60 101 9846 34 19 102 57 70 95 84 63 913 34 39 37 60 81 65 63 9 7148 46 25 50 22 64 91 76 71 79
    8. 8. HOW MANY NUMBERS ARE BELOW 10? 223 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162 55 59 64 33 55 71 58 103 92101 56 45 34 43 15 73 78 6 9339 53 22 26 26 94 60 82 99 7411 12 36 67 70 71 97 59 73 9975 74 69 69 51 48 2 66 92 9815 10 41 58 104 94 92 84 74 8212 52 10 57 33 77 88 81 81 9115 56 25 30 21 7 66 66 78 8729 23 5 34 11 96 74 99 99 8837 10 43 15 50 71 65 60 101 9846 34 19 102 57 70 95 84 63 913 34 39 37 60 81 65 63 9 7148 46 25 50 22 64 91 76 71 79
    9. 9. WHICH QUADRANT HAS HIGHEST TOTAL?23 32 71 72 58 87 11 77 70 1617 21 56 44 68 51 84 20 60 4037 8 107 14 12 41 69 14 18 7162 55 59 64 33 55 71 58 103 92101 56 45 34 43 15 73 78 6 9339 53 22 26 26 94 60 82 99 7411 12 36 67 70 71 97 59 73 9975 74 69 69 51 48 2 66 92 9815 10 41 58 104 94 92 84 74 8212 52 10 57 33 77 88 81 81 9115 56 25 30 21 7 66 66 78 8729 23 5 34 11 96 74 99 99 8837 10 43 15 50 71 65 60 101 9846 34 19 102 57 70 95 84 63 913 34 39 37 60 81 65 63 9 7148 46 25 50 22 64 91 76 71 793
    10. 10. You will be shown a set of numbersalong with a summary (average, etc)Can you make sense of the figures?WHY VISUALISE?
    11. 11. So is the variance in sales.Variance in price is the same.Average sales is the same too.Average price is the same.Take a look at the sales reportalongside. A company hasbranches in 4 cities, and eachbranch changes the productprice every month. This leads toa corresponding change in thesales.Here is the performance of the4 branches with their monthlyprice and sales for each month.Looking at the average, the fourbranches have an identicalperformance.2010 Boston Chicago Detroit New YorkMonth Price Sales Price Sales Price Sales Price SalesJan 10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58Feb 8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76Mar 13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71Apr 9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84May 11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47Jun 14.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04Jul 6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25Aug 4.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50Sep 12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56Oct 7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91Nov 5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89Average 9.0 7.50 9.0 7.50 9.0 7.50 9.0 7.50Variance 10.0 3.75 10.0 3.75 10.0 3.75 10.0 3.75DO THESE FOUR CITIES LOOK IDENTICAL TO YOU?DO YOU AGREE?
    12. 12. ARE THEY REALLY IDENTICAL? CHECK AGAIN…But in fact, the four cities aretotally different in behaviour.Boston’s sales has generallyincreased with price.Detroit has a nearly perfectincrease in sales with price,except for one aberration.Chicago shows a decline in salesbeyond a price of 10.New York’s sales fluctuatesdespite a nearly constant price.Boston ChicagoNew YorkDetroit
    13. 13. 100YEARSOFINDIA’SWEATHER19011911192119311941195119611971198119912001Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
    14. 14. WINNING PARTIESIn the 2004 election to LokSabha there were 1,351candidates from 6 Nationalparties, 801 candidates from36 State parties, 898candidates from officiallyrecognised parties and 2385Independent candidates.The Congress (INC) won145 seats in the 2004elections. BJP won 138,coming a close second.The constituencies whereeach party won is shownhere.Party BJP BSP CPM INC RJD SP
    15. 15. Party BJP BSP CPM INC RJD SPWINNING PARTIESIt is not often easy to seewhich party won the overallelections on a map.In the previous page, BJP (inred), which won inconstituencies with a largephysical area (Rajasthan,Madhya Pradesh), appearedto have swept the elections.This cartogram resizes theconstituencies proportionalto the number of voters, andit’s easier to see that theCongress (in blue) wonabout as many seats as theBJP.
    16. 16. The CandidateTheir CasteTheir PartyWhat do people consider important when voting?Karnataka, Assembly Elections 2008
    17. 17. Top 1/3rdNext 1/3rdLowest 1/3rdSarvagnanagar: 35.7% out of 107941(K J George, INC)Low pollingLow pollingHosakote: 89.3% out of 141953What was the polling percentage?Karnataka, Assembly Elections 2008
    18. 18. 0%10%20%30%40%50%60%70%80%90%100%0 2 4 6 8 10 12 14 16 18# contestantsWinnermarginMore contestants did not reduce the winner marginKarnataka, Assembly Elections 2008
    19. 19. 0%10%20%30%40%50%60%70%80%90%100%0 2 4 6 8 10 12 14 16 18# contestantsRuner-upmarginMore contestants did reduce the runner-up marginKarnataka, Assembly Elections 2004
    20. 20. CRICKETFASTEST SCORERS“I’ve always been curious… whoamong India’s prolific one-dayrun-getters had the best strikerate?Sachin?Sehwag?What about the rest of the world?
    21. 21. INDIAN ODI BATTING
    22. 22. http://gramener.com/cricket
    23. 23. http://gramener.com/cricket
    24. 24. Here are all public Indian companies, grouped by Industry. The size of thebox indicates revenue (2012) and the colour indicates net profit(red is low, green is high). Click on the group to see companies below.
    25. 25. Here are all public Indian companies, grouped by Industry. The size of thebox indicates revenue (2012) and the colour indicates net profit(red is low, green is high). Click on the group to see companies below.
    26. 26. 68% correlationbetween AUD & EURPlot of 6 month dailyAUD - EUR valuesBlock of correlatedcurrencies… clusteredhierarchically
    27. 27. PRE-2009 2009 AND AFTERDecisions to increase the number oflanes on highways grew significantlypost-2009, especially as part of the CCI(Cabinet Committee on Infrastructure)decisionsA significant rise in the number ofdecisions related to the States isseen post 2009 – in contrast withthe focus on “Central” pre-2009The number of internationalagreements has declineddramatically between pre-2009 andpost-2009Decisions related tointervention, assistance and reliefwere almost entirely concentrated inpre-2009
    28. 28. AdultEducationAdminisrativeReformsAgriculturalMarketingAgricultureAnimalHusbandryCooperativeExciseFinanceFisheriesFisheries&InlandwatertransportFood &CivilSuppliesForestFuelHaz &WakfHealthandfamilywelfareHigherEducationHome HorticultureHousingInformation&TechnologyKannada &CultureLabourLaw&HumanRightsMajor &MediumIndustriesMedicalEducationMediumandLargeIndustriesMines&GeologyMinorIrrigationMuzraiP.W.D.ParliamentaryAffairsandHumanRightsPlanningPlanningandStatisticsPrimaryandSecondaryEducationPrimaryEducationPrisonPublicLibraryRevenueRuralDevelopment andPanchayatRajRuralWaterSupplyRuralWaterSupplyandSanitationSericultureSmallScaleIndustriesSmallIndustriesSocialWelfareSugarTextileTourismTransportTransportationUrbanDevelopmentWaterResourcesWoman &ChildDevelopmentYouthandSportsYouthService &SportsBJP focusJD(S)focusINC focusWhat topics did parties focus on during questions?Karnataka, 2008-2012
    29. 29. P.W.D.Health andfamilywelfareRevenueRuralDevelopment andPanchayatRajSocialWelfareUrbanDevelopmentWaterResourcesMinorIrrigationFuelHousingAgriculturePrimaryEducationPrimary andSecondaryEducationWoman &ChildDevelopmentHigherEducationHomeCooperativeForestAdminisrativeReformsLabourFood &CivilSuppliesTourismFinanceAnimalHusbandryTransportationHorticultureMuzraiHaz &WakfTransportMedicalEducationMediumand LargeIndustriesExciseMajor &MediumIndustriesKannada &CultureTextileFisheriesParliamentaryAffairsandHumanRightsAdultEducationRuralWaterSupplyandSanitationMines&GeologySmallIndustriesYouthandSportsSugarPlanning andStatisticsAgriculturalMarketingRuralWaterSupplyFisheries &InlandwatertransportSmallScaleIndustriesYouthService &SportsSericultureLaw&HumanRightsPrisonPlanningInformation&TechnologyPublicLibraryWhat topics did the young & old focus on during questions?Karnataka, 2008-2012Young Old
    30. 30. VISUALISING THE MAHABHARATHA
    31. 31. The only other such times wereFeb 23, 2008 (28 decisions) &Dec 26, 2008 (23 decisions).Nearly two-thirds of decisionsare taken on Thursdaysessions, which is also visibleon the calendar alongside.UPAs best cabinet performance was lastFriday, with a record 23 decisions taken in asingle day, including some long pending keyreform measures.PARLIAMENT DECISIONS (CABINET + CCEA* + CCI**)* CCEA: Cabinet Committee on Economic Affairs** CCI: Cabinet Committee on InfrastructureMon 63 5%Tue 56 4%Wed 105 8%Thu 854 65%Fri 223 17%Sat 6 0%
    32. 32. EDUCATIONPREDICTING MARKSWhat determines a child’s marks?Do girls score better than boys?Does the choice of subject matter?Does the medium of instruction matter?Does community or religion matter?Does their birthday matter?Does the first letter of their name matter?
    33. 33. DistrictGender G BMonth Sep Nov Oct Dec Aug Feb Mar Jan Apr May Jul JunCaste OTHERS CAT-1 ST SCGovt False TrueMedium E K U MHLTWHAT INFLUENCES STUDENTS’ MARKS?
    34. 34. ENGLISH05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
    35. 35. 05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100SOCIAL SCIENCE
    36. 36. 05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100LANGUAGE
    37. 37. 05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100SCIENCE
    38. 38. 05,00010,00015,00020,00025,00030,00035,00040,0000 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100MATHEMATICS
    39. 39. Based on the results of the 20 lakhstudents taking the Class XII examsat Tamil Nadu over the last 3years, it appears that the month youwere born in can make a differenceof as much as 120 marks out of1,200.June bornsscore the lowestThe marks shootup for Aug borns… and peaks forSep-borns120 marks out of1200 explainableby month of birthAn identical pattern was observed in 2009 and 2010…… and across districts, gender, subjects, and class X & XII.“It’s simply that in Canada the eligibilitycutoff for age-class hockey is January 1. Aboy who turns ten on January2, then, could be playing alongsidesomeone who doesn’t turn ten until theend of the year—and at that age, inpreadolescence, a twelve-month gap inage represents an enormous difference inphysical maturity.”-- Malcolm Gladwell, Outliers
    40. 40. BOOKS BY EDWARD TUFTE
    41. 41. We handle terabyte-size data via non-traditional analytics and visualise it in real-time.Gramener visualisesyour dataGramener transforms your data into concise dashboardsthat make your business problem & solution visually obvious.We help you find insights quickly, based on cognitive research,and our visualisations guide you towards actionable decisions.A data analytics and visualisation company
    42. 42. WHAT WE OFFERPLATFORM CUSTOM APPS SERVICESBuy & create yourown visualisationsusing our library ofvisual and analyticalcomponentsWHO’D USE THIS?If you have a stronganalytics & technologyteam, and want tocustomise visualisationsbased on your needsWe build yourdomain-specific BIsolutions to integratevisualisations withyour platformWHO’D USE THIS?If your business needs areclear, you require regularvisual intelligence, butprefer to outsourcedevelopmentWe take yourdata, analyse it, andshare insights thatyou can re-createwith revised datayourselfWHO’D USE THIS?If your needs are unclear, orad-hoc, and you need apartner to help extractactionable insights quicklyout of existing data.
    43. 43. We handle terabyte-size data via non-traditional analytics and visualise it in real-time.Gramener visualisesyour dataGramener transforms your data into concise dashboardsthat make your business problem & solution visually obvious.We help you find insights quickly, based on cognitive research,and our visualisations guide you towards actionable decisions.A data analytics and visualisation company
    44. 44. s.anand@gramener.com+91 9741 552 552

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