We make
Data Analytics
look easy.

Samra Džubur

Lead Data Analyst @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.

SEE OTHER SERVICES

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.

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.

Blogs and Success Stories

movies datasetBlogData Science & AnalyticsTop
January 22, 2020

Turning quantity into quality with movies dataset

Imagine entering the world of analytics Are you a film enthusiast? Can you name all the thrillers released between 2010 and 2015 together with their directors and leading roles? If yes, good for you! (more…)
data science unicornBlogData Science & Analytics
December 11, 2019

Becoming A Data Science Unicorn – Part 2

I hope you have already read the first part of this Series and found your strong WHY, if you have not - you know what to do. Also, if you didn't go through the course I suggested there, AI for everyone, do so now, please. (more…)
data analytics meets qaBlogData Science & Analytics
November 14, 2019

When Data Analytics meets Quality Assurance

Mistakes were made. Let’s acknowledge them The Atlantbh Data Analytics team went through a long and strenuous process of change over the past few years. This evolution, which saw us move from writing reports in (more…)

Let's collaborate

Whether you’re looking for a partner or just want to chat, drop us a message below.