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Zaupanje vodilnih znamk in zagonskih podjetij
Data Analytics is essential to examining information that can help our society as a whole, whether it relates to medicine, consumer trends, or understanding human psychology.
We all know that data is king, and gathering and analyzing the right data can help companies gain exponentially. Hire a data agency today at Freelancer.com to find out what you might be missing.
Brezplačno objavite svoj projekt in se povežite z usposobljenimi Data Analysis Agencies, pripravljenimi da začnejo z delom še danes. Primerjajte ponudbe, ocene in portfelje, plačali pa boste šele, ko boste zadovoljni z delom.
pribl. 70 sek.
do prve ponudbe
61+
ponudb na projekt
265+
Data Analysis Agencies povezanih
Brez stroškov vnaprej, plačate šele, ko ste zadovoljni z delom

9,1
9,1
99%

Salamina, Greece
$44 USD na uro

8,3
8,3
98%

Lahore, Pakistan
$30 USD na uro

9,2
9,2
100%

Umerkot, Pakistan
$100 USD na uro

9,2
9,2
100%

BANGKOK, Thailand
$130 USD na uro

8,5
8,5
99%

KOLKATA, India
$15 USD na uro

9,8
9,8
100%

New Delhi, India
$50 USD na uro

9,2
9,2
99%

dhaka, Bangladesh
$7 USD na uro

8,8
8,8
99%

Chandigarh, India
$35 USD na uro

10,0
10,0
97%

SURAT, India
$15 USD na uro
Želite najeti Data Analysis Agency? To so najbolje ocenjeni Data Analytics projekti, ki so bili nedavno izvedeni na Freelancerju, izbrani med verificiranimi ocenami naročnikov z najmanj 4,5 zvezdicami, ki se mesečno osvežujejo.
PROJEKT
An executive Power BI report was built for a client who praised the work as thorough and detail-oriented. The freelancer carries a 100% completion rate across 61 reviews.
OCENA STRANK
A true professional. Thorough and detail-orientated. I enjoyed working with this freelancer. Looking forward to future projects.
Data Processing · Excel · SQL
PROJEKT
GDP data for two countries was visualized across multiple chart types, including comparative line graphs with statistical annotations and a pie chart of top-five economies for a selected year. A Preferred Freelancer rated 5.0 across 595 reviews completed the work.
OCENA STRANK
Very good work and trustworthy
Python · Data Processing · Statistics
PROJEKT
Python-based data analytics were built for an e-commerce dataset, covering purchase frequency, customer spending tiers, and category profitability using core data structures. The freelancer holds a 100% completion rate across a tenure of 6+ years.
OCENA STRANK
Great to work with Gowri.
Python · Data Processing · Software Architecture
PROJEKT
Twenty-eight Tableau learner submissions were reviewed and graded across ten exam tasks, including forecasting, calculated fields, and dashboard interactivity, with rubric-based feedback written for each. The work was delivered promptly and met expected standards, per the client's review.
OCENA STRANK
Isabella completed the assigned task efficiently and submitted it promptly. She demonstrated good time management, worked independently, and delivered the required work quickly while meeting the expected standards. Her ability to complete the task in a timely manner is commendable.
Data Processing · Excel · Tableau
PROJEKT
Grafana dashboard JSON was built with VictoriaMetrics and Telegraf, covering port status, bandwidth, and host CPU and memory across separate panels. A client_id template variable enabled multi-tenant filtering without any hardcoded IDs.
OCENA STRANK
Spot on, from the first time. Everything I asked for just worked. Great job thank you very much
Statistical Analysis · JSON · API
A data analytics expert is a freelance professional who collects, cleans, models, and interprets data to surface insights that drive measurable business decisions. Hiring a skilled data analytics expert turns raw spreadsheets, transactional logs, and product telemetry into clear answers about customer behavior, revenue performance, and operational efficiency. Whether you need a one-off dashboard, a recurring reporting pipeline, or deep statistical analysis, a freelance data analyst delivers the rigor of an in-house analytics team without the long-term overhead.
A data analytics specialist works across the full analytics lifecycle, from data ingestion to executive reporting. Their core role is translating business questions into queries, models, and visualizations that stakeholders can act on.
Typical engagements involve diagnosing why a metric moved, forecasting future performance, or building self-serve reporting so non-technical teams can answer their own questions. A senior data analyst will also flag data quality issues, recommend tracking improvements, and document methodology so the work is reproducible.
Data analytics freelancers handle a wide range of tasks depending on the maturity of your data stack and the question you need answered. Common deliverables include:
The right tooling depends on your stack, but most experienced analysts are fluent in a recognizable set of platforms. Look for proficiency in:
Almost every sector that produces transactional data benefits from analytics support. Common use cases include:
Strong candidates show evidence of both technical depth and business judgment. Look for portfolio examples that include real dashboards, code samples, written analyses, or anonymized case studies that explain the question, the method, and the outcome. Check ratings, completed project volume, and reviews that specifically mention clarity of communication, since translating findings to non-technical stakeholders is often the hardest part of the job.
Useful interview questions you can copy and use:
Freelancer.com gives you access to a global pool of vetted data analysts, business intelligence developers, and statistical modelers across every time zone and industry. You can review detailed profiles, portfolios, certifications, and verified client reviews before you shortlist, so you hire with evidence rather than guesswork. Clients on Freelancer.com set their own budgets and receive competitive bids, which means you can match the engagement to the scope of your project, whether that is a single dashboard or an ongoing analytics retainer. Milestone Payments hold funds securely until you approve each deliverable, giving you control throughout the engagement.
Hiring a data analytics expert on Freelancer.com is straightforward when your brief is clear and your evaluation criteria are defined. The steps below walk you through writing a strong project post, reviewing proposals, and selecting the right analyst for your data and your business questions.
The quality of your project post is the single biggest determinant of bid quality. A clear brief filters for analysts whose technical stack and domain experience genuinely match the work, and it prevents wasted cycles on candidates who would need to be re-scoped later. Head to the
Bids are short proposals, not just price quotes. They reveal how the analyst interprets your brief, what approach they would take, and whether their proposed timeline is realistic given the data complexity. Read each proposal carefully and shortlist candidates whose understanding of the work matches what you actually asked for.
The final decision combines proposal quality with profile evidence. Strong data analysts show consistent quality across multiple projects, not just a single standout dashboard, and their reviews reflect both technical accuracy and clarity of communication with non-technical stakeholders.
A focused dashboard or one-off analysis often takes one to two weeks, while building a full reporting stack with ETL pipelines and documentation can run several weeks or months. Timelines depend heavily on data quality, the number of source systems, and how clearly the business questions are defined upfront.
Data analysts focus on descriptive and diagnostic work, including SQL, dashboards, and reporting that explain what happened and why. Data scientists lean toward predictive and prescriptive work involving machine learning, experimentation design, and advanced statistical modeling. Many freelancers handle both, but you should match the hire to the question you actually need answered.
Yes. Many engagements on Freelancer.com are short, fixed-scope projects such as building a single Power BI dashboard, cleaning a customer database, or running a specific cohort analysis. You can also extend successful engagements into ongoing retainers if the working relationship is a fit.
Most data analytics freelancers are comfortable working with raw, messy data and will include cleaning and validation as part of their scope. Sharing source files, table schemas, and access to your warehouse or analytics tools early in the engagement speeds up delivery significantly.
A freelancer is usually the right choice when you have a defined question, a single workstream, or want direct communication with the person doing the work. Agencies make more sense for very large, multi-disciplinary programs that require a team of specialists working in parallel.

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