Datacolada

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DataColada is a Salesforce Summit Partner and Stripe Partner with offices in Australia and India. Established in 2015, we have completed 500+ projects to enable business transformation for our customers creating engaging digital experiences at scale. We work closely with our customers to build a long-term relationships and a true partnership where we embark together on a proven transformation journey. We understand the power of the Salesforce platform and that maximising value from technology is a progressive journey. DataColada is a values based professional services and products organisation with a focus on the quad bottom line - people, purpose, planet, profit. We work with healthcare providers, fundraisers, educators, government and professional services organisations, many of whom are registered not for profits. This focus allows us to attract individuals whose personal ambitions include contributing to social good with sustainable solutions in addition to monetary rewards. We see our role in helping organisations succeed in their mission by delivering innovative solutions that add economic and social value in sustainable ways. This goal of creating social benefit is also part of our formal company culture, the “DataColada DNA”, and is represented by our participation in the Pledge 1%. DataColada have pledged to give 1% of our equity, time, profit and product back to the community. Contact us to learn more about how to get more value from Salesforce in your organisation. DataColada, please contact us by phone to: +61 408 833 307 or email: admin@datacolada.com or visit: www.datacolada.com

Company Details

Employees
30
Founded
-
Address
63 York St, Level 4, Sydney,new South Wales 2000,australia
Phone
+61 408 833 307
Email
he****@****ada.com
Industry
Information Technology & Services
Website
datacolada.com
Keywords
Business Processes Improvement, AWS, Service Cloud, Sales Cloud, Salesforce Integration, Salesforce, Website Design, Pardot, Experience Cloud, Marketing Cloud, Commerce Cloud, CPQ and Billing, Full Stack Development, AppExchange Product Build, Managed Services, Generative AI, Stripe, Payments.
HQ
Sydney, New South Wales
Competitors
Pacific Point, Sauce, Salesforce, Sopra Steria, Bong Bong Academy, Dawn Digitech, Cloudwerx, Comet CX, 8Squad, KaizenIT Infotech.
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Datacolada Questions

News

[98] Evidence of Fraud in an Influential Field Experiment About Dishonesty - Data Colada

[98] Evidence of Fraud in an Influential Field Experiment About Dishonesty Data Colada

[70] How Many Studies Have Not Been Run? Why We Still Think the Average Effect Does Not Exist - Data Colada

[70] How Many Studies Have Not Been Run? Why We Still Think the Average Effect Does Not Exist Data Colada

[116] Our (First?) Day In Court - Data Colada

[116] Our (First?) Day In Court Data Colada

[114] Exhibits 3, 4, and 5 - Data Colada

[114] Exhibits 3, 4, and 5 Data Colada

[112] Data Falsificada (Part 4): "Forgetting The Words" - Data Colada

[112] Data Falsificada (Part 4): "Forgetting The Words" Data Colada

[113] Data Litigada: Thank You (And An Update) - Data Colada

[113] Data Litigada: Thank You (And An Update) Data Colada

[118] Harvard’s Gino Report Reveals How A Dataset Was Altered - Data Colada

[118] Harvard’s Gino Report Reveals How A Dataset Was Altered Data Colada

[105] Meaningless Means #1: The Average Effect of Nudging Is d = .43 - Data Colada

[105] Meaningless Means #1: The Average Effect of Nudging Is d = .43 Data Colada

[89] Data Replicada #6: The Problem of (Weird) Differential Attrition - Data Colada

[89] Data Replicada #6: The Problem of (Weird) Differential Attrition Data Colada

[111] Data Falsificada (Part 3): "The Cheaters Are Out of Order" - Data Colada

[111] Data Falsificada (Part 3): "The Cheaters Are Out of Order" Data Colada

[106] Meaningless Means #2: The Average Effect of Nudging in Academic Publications is 8.7% - Data Colada

[106] Meaningless Means #2: The Average Effect of Nudging in Academic Publications is 8.7% Data Colada

[126] Stimulus Plots - Data Colada

[126] Stimulus Plots Data Colada

[90] Data Replicada #7: Does Displaying Multiple Copies of a Product Increase Its Perceived Effectiveness? - Data Colada

[90] Data Replicada #7: Does Displaying Multiple Copies of a Product Increase Its Perceived Effectiveness? Data Colada

[121] Dear Political Scientists: Don't Bin, GAM Instead - Data Colada

[121] Dear Political Scientists: Don't Bin, GAM Instead Data Colada

[99] Hyping Fisher: The Most Cited 2019 QJE Paper Relied on an Outdated Stata Default to Conclude Regression p-values Are Inadequate - Data Colada

[99] Hyping Fisher: The Most Cited 2019 QJE Paper Relied on an Outdated Stata Default to Conclude Regression p-values Are Inadequate Data Colada

[78a] If you think p-values are problematic, wait until you understand Bayes Factors - Data Colada

[78a] If you think p-values are problematic, wait until you understand Bayes Factors Data Colada

[21] Fake-Data Colada: Excessive Linearity - Data Colada

[21] Fake-Data Colada: Excessive Linearity Data Colada

[110] Data Falsificada (Part 2): "My Class Year Is Harvard" - Data Colada

[110] Data Falsificada (Part 2): "My Class Year Is Harvard" Data Colada

[115] Preregistration Prevalence - Data Colada

[115] Preregistration Prevalence Data Colada

[77] Number-Bunching: A New Tool for Forensic Data Analysis - Data Colada

[77] Number-Bunching: A New Tool for Forensic Data Analysis Data Colada

[103] Mediation Analysis is Counterintuitively Invalid - Data Colada

[103] Mediation Analysis is Counterintuitively Invalid Data Colada

[73] Don't Trust Internal Meta-Analysis - Data Colada

[73] Don't Trust Internal Meta-Analysis Data Colada

[1] "Just Posting It" works, leads to new retraction in Psychology - Data Colada

[1] "Just Posting It" works, leads to new retraction in Psychology Data Colada

[88] The Hot-Hand Artifact for Dummies & Behavioral Scientists - Data Colada

[88] The Hot-Hand Artifact for Dummies & Behavioral Scientists Data Colada

[95] Groundhog: Addressing The Threat That R Poses To Reproducible Research - Data Colada

[95] Groundhog: Addressing The Threat That R Poses To Reproducible Research Data Colada

[20] We cannot afford to study effect size in the lab - Data Colada

[20] We cannot afford to study effect size in the lab Data Colada

[91] p-hacking fast and slow: Evaluating a forthcoming AER paper deeming some econ literatures less trustworthy - Data Colada

[91] p-hacking fast and slow: Evaluating a forthcoming AER paper deeming some econ literatures less trustworthy Data Colada

[27] Thirty-somethings are Shrinking and Other U-Shaped Challenges - Data Colada

[27] Thirty-somethings are Shrinking and Other U-Shaped Challenges Data Colada

[67] P-curve Handles Heterogeneity Just Fine - Data Colada

[67] P-curve Handles Heterogeneity Just Fine Data Colada

[74] In Press at Psychological Science: A New 'Nudge' Supported by Implausible Data - Data Colada

[74] In Press at Psychological Science: A New 'Nudge' Supported by Implausible Data Data Colada

[36] How to Study Discrimination (or Anything) With Names; If You Must - Data Colada

[36] How to Study Discrimination (or Anything) With Names; If You Must Data Colada

[64] How To Properly Preregister A Study - Data Colada

[64] How To Properly Preregister A Study Data Colada

[79] Experimentation Aversion: Reconciling the Evidence - Data Colada

[79] Experimentation Aversion: Reconciling the Evidence Data Colada

[58] The Funnel Plot is Invalid Because of This Crazy Assumption: r(n,d)=0 - Data Colada

[58] The Funnel Plot is Invalid Because of This Crazy Assumption: r(n,d)=0 Data Colada

[23] Ceiling Effects and Replications - Data Colada

[23] Ceiling Effects and Replications Data Colada

[47] Evaluating Replications: 40% Full ≠ 60% Empty - Data Colada

[47] Evaluating Replications: 40% Full ≠ 60% Empty Data Colada

[18] MTurk vs. The Lab: Either Way We Need Big Samples - Data Colada

[18] MTurk vs. The Lab: Either Way We Need Big Samples Data Colada

[63] "Many Labs" Overestimated The Importance of Hidden Moderators - Data Colada

[63] "Many Labs" Overestimated The Importance of Hidden Moderators Data Colada

[37] Power Posing: Reassessing The Evidence Behind The Most Popular TED Talk - Data Colada

[37] Power Posing: Reassessing The Evidence Behind The Most Popular TED Talk Data Colada

[51] Greg vs. Jamal: Why Didn’t Bertrand and Mullainathan (2004) Replicate? - Data Colada

[51] Greg vs. Jamal: Why Didn’t Bertrand and Mullainathan (2004) Replicate? Data Colada

[43] Rain & Happiness: Why Didn’t Schwarz & Clore (1983) ‘Replicate’ ? - Data Colada

[43] Rain & Happiness: Why Didn’t Schwarz & Clore (1983) ‘Replicate’ ? Data Colada

[13] Posterior-Hacking - Data Colada

[13] Posterior-Hacking Data Colada

[11] “Exactly”: The Most Famous Framing Effect Is Robust To Precise Wording - Data Colada

[11] “Exactly”: The Most Famous Framing Effect Is Robust To Precise Wording Data Colada

[30] Trim-and-Fill is Full of It (bias) - Data Colada

[30] Trim-and-Fill is Full of It (bias) Data Colada

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