We make
Data Analytics
look easy.

Samra Džubur

Data Analyst Manager @Atlantbh

Meet Samra and other Atlanters>
SERVICES

Data Analytics

We help you turn raw data, delivered in various formats and knowledge domains, into meaningful insights. While the process is highly automated, we consistently include an individual analyst’s perspective, which takes into account your specific business requirements and goals, ensuring we provide you with the best possible solutions based on your data set. Subsequently, we are able to deliver an array of statistical overviews, data quality issue detections and recommendations for data-driven decision making.

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Technology stack

We specialize in a wide range of technological solutions relating to Data Analytics to tackle any data set. When necessary, we can also provide Data Science solutions.

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Tableau
Hive
scala
Python

What we do

We offer a comprehensive kit of Data Analytics services to convert your data into actionable insights. Whether you have historical or real-time data, traditional Big Data, we can accommodate your business needs and offer transparency and flexibility throughout the process.

  • Data preprocessing
  • Data visualization
  • Issue detection
  • Pattern recognition
  • Data comparison
  • Statistical reports
  • Data quality reports
  • Recommendation delivery
  • Development of custom analyses

How we do it

Data is a numbers game and we make sure the figures always add up.

1

Defining Analysis Goals

Communication with our clients is essential when defining analysis goals. Just like our conclusions are used in the client's decision-making process for business needs, the client's feedback is used in our decision-making process when choosing an analysis approach. There are many perspectives to a single problem, we use the client's specific requirements and input to help us choose the adequate perspective.
2

Defining Analysis Steps

After defining the goal of the analysis, we proceed with creating precise steps for answering the analysis questions. However, we do not implement them before checking their logic flow with other teammates.
3

Improving the Analysis Process

While there are many perspectives on a single problem, there are also many problems that have not been identified earlier. This is a typical use case for when we need to improve our current analyses or create new ones. The first step is to create a Proof of Concept (POC), which we present to our clients and, of course, consult with the whole team during the process.
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Blogs and Success Stories

The Simplest League of Legends Champion AnalysisData Science & AnalyticsTech Bites
August 4, 2022

The Simplest League of Legends Champion Analysis

What is League of Legends? League of Legends is a 2009 MOBA (multiplayer online battle arena) video game made by Riot Games. It is one of the most popular video games, having 3.5 million daily active players. In the game, two teams of five players battle in player-versus-player combat, each team…
Omar Celik 0
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TITANIC DISASTER THROUGH DATA ANALYSISBlogData Science & Analytics
July 22, 2022

Titanic Disaster Through Data Analysis

The well-known passenger ship Titanic, for which there were rumors that it was “unsinkable,” had a severe accident in 1912. after hitting an iceberg on its first trip. It is estimated that there were 2,224 passengers on the ship, and more than 1,500 people died, which made this one of…
Amina Poplata 0
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Combining UX principles with Data AnalysisData Science & AnalyticsTech Bites
June 10, 2022

Combining UX principles with Data Analysis

How to perfect your data visualization with simple UX principles Friedrich von Schlegel’s “Every art should become science and every science should become art,” might sound a little over-exaggerated, but he does have a point - combining artistic and scientific approaches can only lead to something exceptional! When talking about…
Lejla Vardo 0
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Let's collaborate

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