Data Science Development Company

Daily activities of a data scientist include research and writing algorithms or code. Teamwork is an integral part of the process – several specialists join forces to find, source, clean, structure, analyze and understand the data. Data scientists help solve various business problems by discovering the right questions to answer and related sets of information. Companies use data science for sustainable development of various projects – for example, to find the most efficient way to conduct AWS and Google Cloud migration without serious risks and problems. The final result of the specialists’ work is a comprehensive report that answers questions, proves hypotheses, validates ideas, etc.

Data science solutions building starts with defining and problems and finding data sources, followed by different processes to transform the data and then create custom models that can provide answers to the stated problems.

A business question is the main reason to look for data science service providers. Your question or challenge may be related to your current reporting tool, or the level of customer services, or employee productivity, or anything else. The important factor is your belief that the answer to this query lies in your company data. In this case, skilled data scientists will be able to analyze your current situation, find valuable information hidden within big data, make sense of what they found, and prepare visualizations for stakeholders to understand and make better decisions.

When it comes to data science business development, there is a whole lifecycle which means conducting a wide range of processes with various tools. A typical project includes these four stages:

1. Collecting data. First of all, a data science specialist collects all kinds of data using different methods such as scraping, streaming from different systems, etc. Some pieces may have structure (customer data) while others come unstructured (video, audio, pictures, real-time data from IoT devices, etc.), and there can be different formats too.
2. Storing and processing data. Specialists create standards and workflows to handle the data properly and prepare it for analysis. At this stage, there are different processes like cleaning, making copies, loading, transforming, etc.
3. Analyzing data. Data scientists carry out various kinds of studying, modeling, evaluation, A/B tests, pattern search, etc. They use Machine Learning, predictive analytics, Deep Learning, etc. We provide data science as a service – companies from various industries approach us for solutions that can help them find answers to specific business-related questions.
4. Reporting and visualization of data. Everything valuable that specialists find becomes reports and visualizations. Later, business analysts can work with this information and base their decision on it.

Consulting on problems related to data science can mean all kinds of advice. For example, a company may want to consult on the best ways to analyze information before starting complex processes like system integration or business automation. Consultation services are always based on expertise of specialists in neural networks, machine learning, predictive analytics, big data, etc. Moreover, data science consulting services are based on a profound analysis and understanding of the company’s problems and strategic goals.

Data analysis is an integral part of customer success strategies, security checking, fraud prevention, etc. For example, an insurance company may use the services of a data science development firm to gather and study customer banking history, housing conditions, health information, accident statistics, and other pieces of data to decide which kind of insurance policy they can offer. Other industries that benefit from data science services are Banking, Retail, Healthcare, Education, Real estate, and more.

There are three main processes of data transformation – collecting, structuring, and analysis. All of these are included in the data science model development life cycle.

What are the 4 types of data science? Data science includes several primary branches: Computer science, Machine learning , Data analysis, and Statistics. Each branch influences the process of handling information in different unique ways.