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Hiring a Freelance Data Analyst

Why and when you need a Data Analyst?

Who is able to identify the business needs and recognize how data science can address them? The Data Analyst or business analyst is a type of consultant whose goal is to improve the results of the company by using data, that is, create a data driven organization.

A data analyst consultant defines the business needs, works together with the business and with data scientists to assess, analyze and define application strategies to achieve an impact, across any area of the organization but usually with a focus on commercial activities to drive revenue, operations to bring costs down and improve service and on quality and innovation.

What is not defined cannot be measured. What is not measured can not be improved. What is not improved, is always degraded. - William Thomson Kelvin

Through Outvise you can find skilled and certified data analyst freelancers or consultants and pay only for the services delivered.

Case studies with Data analyst

Certified Data analysts in the Network

case study
Data analyst case study for a global beverage company on quality

Challenge, Context, Problems to be solved

Integrate all sales reports in SAP across countries.

Mission, tools and methodology

Securely and quickly integrate all sales information unifying data in the different territories. We ensured the quality of the data with Alteryx.

Achieved results

Management receives for the first time integrated and comparable reports of all European territories.

Francesc
Computer Science and Engineering

case study
Data analyst use case for an electric manufacturer on integrating information from different sources

Challenge, Context, Problems to be solved

A global specialist in energy management and automation with 135K employees had a lot of scattered information. This made it impossible to develop any cost optimization strategy.

Mission, tools and methodology

To start any analytical project they needed a data repository with information from different sources (CRMs, ERPs, etc).

The data warehouse was restructured so that the system could be used for any analytical project the information needed (understand per country what products were returned, shipping costs, etc).

Achieved results

In 7 months, a well built and organized data warehouse for head office to start developing analytical projects to optimize costs was created.

7 months
Francesc
Computer Science and Engineering

case study
Data analyst use case for a retailer on optimizing their sales campaigns

Challenge, Context, Problems to be solved

A French retailer selling products through online flash sales wanted to get information from their competitors to optimize their campaigns.

Mission, tools and methodology

They hired a scrapper to analyze the demand and % the brands were negotiating with their competitors.

This is one of the most demanded techniques by retailers worldwide, being 18% of ecommerce visits bots, buying tickets or any type of product.

We created dashboards that were then integrated with the product catalogs and crossed with the results to do all the monitoring of the campaign.

Achieved results

They were able to compare their own campaigns with the competition to improve conversion with better prices, anticipation, new trends, customer knowledge, etc.

France
Francesc
Computer Science and Engineering

case study
Data analyst use case for an European job search portal

Challenge, Context, Problems to be solved

The commercial director of one of the largest online job search portals in Europe needed help with pricing and product optimization.

The commercial offer was very different as they worked with all types of accounts, for example, staffing companies needing hundreds of CVs a year and SMEs looking for a few profiles only.

Mission, tools and methodology

The data analyst freelancer had to optimize the different prices per CV - cross use of CV with cost for what they paid. And from there the commercial team could work on the proposals they had to offer.

The work was to join 2 separate databases to obtain normalized metrics of the consumption of payments (monthly, quarterly, etc.) resulting in a matrix with 2 axes - CV consumption with costs.

Achieved results

The CV average cost that would have a good competitiveness in the market could be determined. This allowed the company to know the profitability of each client, the commercial workload needed, and adapt their prices and products to different clients.

Europe
Francesc
Computer Science and Engineering

case study
Data analyst use case for a software and app discovery portal to optimize their sales funnel

Challenge, Context, Problems to be solved

The world's largest software and app discovery platform wanted to optimize their sales funnel. With over 100 million users per month and more than 4 million downloads per day they needed to understand the whole buying journey to increase sales.

Mission, tools and methodology

A BI tool has been designed and implemented to unify the KPIs of all channels and thus enabling a global vision.

The business model is based on downloading software with different subscription models and the dashboard had to collect all visits, leads, subscriptions, sales, cancellations, etc.

Achieved results

The customer conversion funnel has been optimized:

  • By being able to measure all the relevant metrics in each channel and for each product.
  • The dashboard shows the information in real time, which allows making quick and effective decisions.

Francesc
Computer Science and Engineering

Must have Data Analyst Skills

Data analysts must have strong capabilities on both technical and strategical aspects of the data practice:

  • Business analytics and business intelligence
  • Great understanding of the business
  • Data science and engineering

The technical knowledge of a data analyst should include the command of various of the following solutions, frameworks and languages:

  • Snowflake · AWS · Google Cloud/AI · MS Azure · IBM Watson · Oracle · Hadoop · SAS · Splunk · Kubernetes · SAP Hana · Elastic · Salesforce
  • Qlikview · Tableau · Alteryx · Trifacta . Power BI · Google Analytics
  • Python · Java · R · Spark · SQL · MQL