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.

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
  • Predictive analysis

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

Unleashing the Power of AI in Product Development, Samra TanovicData Science & AnalyticsProduct ManagementTop
July 24, 2023

Unleashing the Power of AI in Product Development

Lately, we have seen a significant number of discussions regarding the potential of AI and strategies to incorporate it into the product development process. Specifically, how can we enhance, innovate, and scale in ways we were not able to do before? In this interview, we asked Samra Tanovic, our VP…
Clustering Algorithms: DBSCAN vs. OPTICSData Science & AnalyticsTech Bites
July 5, 2023

Clustering Algorithms: DBSCAN vs. OPTICS

Nowadays, we live in a world of data, which means we are constantly surrounded by enormous amounts of data. Data is generated by everything we do, both online and offline, from our internet activities and purchases to our physical motions and interactions. This data contains valuable insights and knowledge that…
Random String DetectionBlogData Science & Analytics
May 15, 2023

Random String Detection

What are Random Strings? Data analysis often presents us with the challenge of dealing with noisy inputs. This is particularly evident when working with large datasets of user inputs. Detecting and filtering out random string inputs can prove invaluable in various scenarios, such as data validation, quality control or the…

Let's collaborate

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