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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client
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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 role of Data Analytics in the function of Map QualityData Science & AnalyticsTech Bites
January 18, 2023

The role of Data Analytics in the function of Map Quality

What is a map? A map is a symbolic representation of selected characteristics of a place, usually drawn on a flat surface. Maps represent information about our world in a simple, visual way. They teach about it by showing the sizes and shapes of countries, locations of features, and distances between…
Bakir Sujoldzic 0
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Data-centric AI / Big data vs. Good dataBlogData Science & Analytics
January 10, 2023

Data-centric AI / Big data vs. Good data

We can agree that AI is not a one-size-fits-all solution. However, for many companies, AI can provide significant benefits and help drive growth and success. Some potential benefits include the following: Improved efficiency: AI can automate tasks and processes, saving time and resources for other activities. Increased accuracy: AI can…
Mehmed Kadric 0
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How to Ensure Data Integrity?Data Science & AnalyticsTech Bites
December 14, 2022

How to Ensure Data Integrity?

The World of Data If one were to look at the world's highest-performing companies right now by market cap, one'd notice that 4 out of the top 5 are massive tech companies, with one oil conglomerate sneaking in. It is no surprise then to hear huge news outlets, such as…
Ferid Omic 0
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