- The Number: 700 on a 1-1000 Scale
- Why 700 Is Not "70 Percent"
- Exam Mechanics Behind the Score
- Where Your Points Come From: The Five Domains
- What Certiport Does Not Publish
- Turning 700 into a Readiness Target
- Fees, Vouchers and the Cost of a Miss
- After You Pass: Validity and Recertification
- Frequently Asked Questions
- The passing score for IT Specialist - Data Analytics is 700 on a scaled 1-1000 range.
- 700 is a scaled score, not a raw 70 percent requirement, so counting correct answers is unreliable.
- The exam has an estimated 35-45 questions in a 50-minute maximum, and the question count varies.
- Certiport does not publish pass rates, and the five objective headings carry no official percentage weights.
The Number: 700 on a 1-1000 Scale
To earn the IT Specialist - Data Analytics credential (abbreviated ITS-DA on this site), you need a score of 700 on a scale of 1 to 1000. The exam is issued by Pearson and administered through Certiport, a Pearson VUE business. That single figure is the only passing threshold the program publishes, and it applies to the exam as a whole rather than to each section separately.
Everything else people repeat about this score, such as "you need 70 percent" or "you can miss exactly N questions," is inference. This article separates what is documented from what is guesswork, so you can plan your preparation around real facts. If you want the broader picture of how the exam fits together, the ITS-DA Exam Domains 2026: Complete Guide to All 5 Content Areas covers each objective area in depth.
Why 700 Is Not "70 Percent"
The most common misreading of a 700/1000 passing score is that it equals 70 percent correct. It does not. A scaled score is produced by a conversion process that maps your performance onto a fixed reporting range. Two candidates who answer the same number of questions correctly may not receive identical scaled scores if their question sets differ, because the exam draws a variable number of items and forms are not guaranteed to be identical in difficulty.
For a Data Analytics candidate, this has practical consequences:
- You cannot compute a safe "miss budget." If your form has 35 questions, you cannot assume a fixed number of misses is acceptable. The official sources do not publish a raw-to-scaled conversion table.
- Question count varies. The exam listing estimates 35-45 questions, which is a range, not a fixed form size. Do not train for exactly 40 items.
- Not every item behaves the same. Some questions may be interactive or multi-part rather than simple single-answer items, which is another reason raw tallies mislead.
The healthy mindset is to aim for solid mastery across all five areas instead of trying to engineer a minimum number of correct answers. Our How Hard Is the ITS-DA Exam? Complete Difficulty Guide 2026 explores how that plays out in practice.
Exam Mechanics Behind the Score
Your score is generated under specific delivery conditions. Understanding them removes surprises that can cost points for reasons unrelated to knowledge.
| Exam Element | What the Sources State |
|---|---|
| Passing score | 700 on a 1-1000 scaled range |
| Question count | Estimated 35-45 questions; a variable range, not a fixed count |
| Time limit | 50-minute maximum of timed exam time |
| Delivery | Computer-based, proctored, via Pearson VUE test centers, OnVUE online proctoring, or a Certiport Authorized Testing Center (CATC) |
| Exam-only fee (MindhubPro) | USD 127 web/member pricing displayed |
| Pass rate | Not published by Certiport |
The 50-minute clock
The 50-minute limit refers to timed exam time. Administrative steps and the tutorial are not counted against it, per Certiport's exam-length guidance. That still leaves a tight pace: with an estimated 35-45 questions, you are working at roughly a minute and change per item on average. Questions involving reading a SQL query, interpreting a Python or R snippet, or evaluating a chart take longer than a definition recall question, so you need to bank time on the easy ones.
Interface conventions
The IT Specialist Exam Tutorial (a 2021 document) describes how answer-option navigation works in the testing interface. Note that its generic 36-40-question estimate is older than the exam-specific 35-45 range used here, so treat the tutorial as an interface reference rather than a source for question count. Familiarity with how to select, change and review answers means you spend your 50 minutes on analytics, not on fumbling with the screen.
Proctoring and testing channels
You can test at a Pearson VUE center or through OnVUE online proctoring, which requires a system check and a live webcam proctor. A separate route runs through a Certiport Authorized Testing Center (CATC). CATC conditions include photo and signature ID, a non-disclosure agreement, parental consent for candidates under 18, and no personal paper or communication devices in the room. A configuration or ID problem on test day will not reduce your scaled score, but it can cost you the appointment, so verify everything beforehand. For scheduling details, see ITS-DA Exam Dates 2026: Testing Windows, Deadlines & Scheduling.
Where Your Points Come From: The Five Domains
The exam objectives list five headings. Pearson's document presents these as official exam objectives, not as a preparation curriculum, and no official percentage weights are published. That means any article claiming "Domain 3 is 30 percent of your score" is making up a number. What you can say is that all five areas are fair game, and a 700 requires competence across the board rather than brilliance in one.
Domain 1: Data Basics
The foundation: understanding what data is and how it is structured and represented before you analyze it.
- Current coverage includes date/time handling and tuples as data structures
- Be able to recognize data types and structures in SQL, R, Python and Excel contexts
Domain 2: Data Manipulation
Cleaning, transforming and querying data using the tools the objectives name.
- SQL querying is part of current coverage
- Excel with Power Query, plus R and Python, appear in the scope
- Expect to read code or steps and identify the resulting output or the correct transformation
Domain 3: Data Analysis
Applying analytical techniques to find patterns and draw conclusions.
- Principal component analysis, cluster analysis and association analysis are named in current coverage
- The outline covers basic AI/ML roles in analysis but explicitly excludes specific machine-learning algorithms, so do not spend time memorizing algorithm internals
Domain 4: Data Visualization and Communication
Choosing the right chart and conveying findings honestly.
- Coverage includes Sankey diagrams and box plots
- Recognizing misleading charts is explicitly in scope
Domain 5: Responsible Analytics Practices
The ethics and limits of analysis.
- Privacy and small-sample anonymity concerns
- Bias and the limits on generalizing from your data
The current coverage above matches the additions announced in Certiport's "Preparing for the future: IT Specialist exam updates" post dated May 14, 2025. That post still uses future-tense "fall" wording and gives no exact release date, so this article does not claim a specific exam version or launch date. If you want a deeper walk through each area, the ITS-DA Study Guide 2026: How to Pass on Your First Attempt maps study activities to these headings.
What Certiport Does Not Publish
A trustworthy passing-score article has to be clear about gaps. Here is what is not available from official sources, so you should be skeptical of any site claiming otherwise:
- Pass rates. Certiport does not publish them. See ITS-DA Pass Rate 2026: What the Data Shows for how to think about this honestly rather than relying on invented percentages.
- Domain weightings. No official percentages exist for the five headings.
- A raw-score conversion. There is no published table mapping number of correct answers to a scaled score.
- A numbered exam revision. No exam version number is published, and the Pearson objectives PDF's copyright date should not be treated as a release date.
Because of these gaps, your preparation should rest on the objectives themselves. Treat the official objectives document as the authoritative scope statement and build practice around it.
Turning 700 into a Readiness Target
Since you cannot reverse-engineer a raw cutoff, define readiness behaviorally. The program suggests approximately 150 hours of preparation, and objective profiles describe at least 150 hours. These are readiness profiles, not a verified logged-hours application requirement. Nobody checks your hours, but the figure is a useful planning anchor if you are starting from limited data experience. No degree is required beyond knowledge of the objective domains; see ITS-DA Requirements 2026: Eligibility, Prerequisites & How to Qualify for the full picture.
One sensible way to sequence that effort is to front-load the areas that everything else depends on, and to save judgment-heavy topics for when your technical base is stable:
Data Basics and Manipulation
- Practice date/time handling, tuples, and basic data types
- Write and read SQL queries; work through Excel Power Query steps
- Read short R and Python snippets and predict their output
Data Analysis
- Learn what principal component, cluster and association analysis are used for and how to interpret their results
- Understand the basic role of AI/ML in analysis without memorizing specific algorithms
Visualization and Responsible Practice
- Match scenarios to chart types, including Sankey diagrams and box plots
- Spot misleading charts; review privacy, small-sample anonymity, bias and generalization limits
Timed Mixed Practice
- Run full-length practice under a 50-minute limit with a mix of domains
- Review every miss by domain and revisit the weakest area
Key Takeaway
Aim to be comfortably strong in all five domains rather than perfect in two. Because the 700 is a scaled score over an unpublished conversion, a thin margin in any area is a risk you cannot measure. A one-page review such as the ITS-DA Cheat Sheet 2026: One-Page Review of Must-Know Facts helps you keep the cross-domain details fresh in the final days.
To test where you actually stand against this scope, work through realistic questions on the ITS-DA practice test site, then use your results to decide which phase deserves another pass. Timed practice matters here: a candidate who knows the material but reads slowly can still run short against the 50-minute maximum.
Fees, Vouchers and the Cost of a Miss
The passing score matters more once you consider what a failed attempt costs. Pearson MindhubPro displays USD 127 web/member pricing for the exam-only voucher. A few mechanics are worth knowing:
- The voucher is country-restricted and unavailable in some listed markets, so confirm availability for your location before buying.
- The voucher expires 12 months after purchase. This is separate from credential validity; it only governs how long you have to use the voucher.
- An alternative exists: a USD 133, US-only CATC voucher that includes a retake. Proctoring may cost extra, and this voucher cannot be used at Pearson VUE centers or through OnVUE.
The retake-inclusive CATC option can be attractive if you are nervous about clearing 700 on the first try, but only if you can test through an Authorized Testing Center in the US. Weigh it against the exam-only route using the ITS-DA Certification Cost 2026: Complete Pricing Breakdown. If you are weighing whether the credential justifies the spend at all, Is the ITS-DA Certification Worth It? Complete ROI Analysis 2026 addresses that question.
After You Pass: Validity and Recertification
Reaching 700 earns a credential with a defined lifespan. For awards on or after 2025-06-18, validity is five years. Awards earned before that date remain nonexpiring. Recertification requires a new voucher and passing the current exam, which means the content you face the second time may differ from what you studied originally, especially given the maintained, ongoing updates to IT Specialist exams.
For employers, a passed Data Analytics exam signals applied familiarity with SQL, scripting in R and Python, spreadsheet-based transformation and honest data communication. It reads as an entry-level proof point rather than a senior credential. To see how that translates into roles and compensation, browse ITS-DA Jobs and the ITS-DA Salary Guide 2026: Complete Earnings Analysis.
Frequently Asked Questions
The passing score is 700 on a scaled range of 1 to 1000. It applies to the exam overall, and Certiport describes it as a scaled score rather than a raw percentage.
No. A scaled score is converted from your performance, and no raw-to-scaled conversion table is published. Because the exam has a variable question range of about 35-45 items, you cannot reliably compute a minimum number of correct answers.
The MindhubPro listing estimates 35-45 questions with a 50-minute maximum. That is a variable range, not a fixed count, and the 50 minutes is timed exam time excluding administration and tutorials.
No official percentage weights are published for Data Basics, Data Manipulation, Data Analysis, Data Visualization and Communication, or Responsible Analytics Practices. Prepare for all five rather than assuming any one dominates.
You would need another voucher or attempt to retest, so the cost matters. The exam-only voucher is USD 127 on MindhubPro, while a US-only CATC voucher at USD 133 includes a retake. Review the study guide and your weak domains before booking again.