Data science services assist businesses in conducting experiments on their data in order to gain business insights. To satisfy our clients’ most purposeful analytics demands, iSummation data science service company provides data science consulting using Machine Learning, Artificial Intelligence, and Deep Learning technologies.
How Does Data Science Works?
Data science is a field that uses a variety of scientific methodologies to extract knowledge and obtain insights from data. Data scientists analyze raw data and modify it using advanced methodologies and a wide range of experience. A data science team should have expertise in a variety of subjects, including mathematics, engineering, computing, visualization, and statistics. They can extract important insights and information from large amounts of data thanks to their skill. This data could include the most critical pieces of information for your company.
The first step of data science deals with how data is collected from different platforms. Data and insights are always distributed across a variety of corporate systems and apps; it is never in one place. New data can be collected into a system and this process can be either manual or automated.
The second step deals with what happens to the data once it is sourced. Well, this process of data warehousing stores data captured from different sources. Then, inaccurate, unused, duplicate, and missing data is removed from the database.
Data mining is the third step and it is used to identify trends and future patterns in data science. Processed data is then divided into groups on the basis of similar traits. However, this data is used to produce to descriptive diagram that shows the relationship between different types of data.
After classifying the data, the fourth step is to analyze the data. Using data analytics tools experts can help make predictions based on the data. Data analysis can also be done using text mining, regression, and qualitative analysis methods available in the tech world.
It is important to display the results of your data mining and analysis to gain utility from the data. The last step can be done using reports consisting of the results of research and analysis of the data.
Our Data Science Service Offerings
iSummation as your data science solutions company offers end-to-end data science services to help you get the value of your data. Just share your data in the hands of trusted companies like us and we will handhold you to decode it.
We are experts in enriching and collecting the data preparation processes by missing value replacement, outlier analysis.
Our data science experts generate, test, and refine model-based data on the basis of the validity of the output.
We do a migration of different algorithms models from one platform to the other.
Appropriate, Accurate scope identification, feasibility assessment.
Why iSummation as your Data Science Company?
- We always begin by gaining a thorough grasp of the client’s business needs, goals, and data resources, among other things. We only create models that are completely tailored to your needs.
- We assist in determining which business problems could be tackled more effectively with AI and which areas machine learning can provide the greatest return on investment.
- We have a lot of expertise in creating, training, and deploying several sorts of Machine Learning algorithms.
- We hire people with rare and unique ML skillsets; for example, we’re well-versed in Topological Data Analysis and how to use data decomposition to increase the accuracy of ML models.
- TensorFlow, Keras, Pytorch, Scikit-learn, Caffe, and other prominent machine learning frameworks are among our specialties.
iSummation’s Data Science Project Flow
Data Science Consulting
This first stage entails a quick discussion with our data science team about the topic. We’ll look at the data, ask the major questions, and set any project objectives. Our data science company experts also take the time to explain what opportunities are available as well as the potential dangers of machine learning deployment.
Analysis & Preparation of Data
Our data engineers will carefully review the data sets you’ve provided after we’ve laid the framework to guarantee they chose the proper one. To prepare a dataset for the future model, they’ll clean the data and engage in feature engineering. For data mining and analysis, we mix traditional Agile concepts with the latest model. A typical cycle focuses on one hypothesis to achieve task and result precision.
Modelling & Training
The data science team will begin to create and train models using prepared data to test the hypothesis at this point. The data science team based in USA, UK, and India will conduct multiple tests in order to find a balance between accuracy and computer resource usage. This stage’s purpose is to provide tangible outcomes in the shortest amount of time possible in order to prove the hypothesis.
Evaluation & Changes
Our data engineers will continue to adjust and optimize the selected model after we’ve proven the hypothesis through raw modeling. This step will enhance overall accuracy while also consuming less power and time.
Integration and Deployment
Our data science services pros put the model on a test server when we’ve verified it, so it can start working with real data and we can track the outcomes. If the model works well and achieves your business objectives in the test environment, we will deploy it in production.
Covered Domain Areas
- Artificial Intelligence
- Big Data
- Machine Learning
- Natural Language Processing
- Computer Vision
- Data Mining
Tools and Technologies
Amazon Web Services
IBM Watson Studio
Industries that can Benefit from Data Science Consulting
We work with all-size businesses— from startups to Fortune500— in industries from marketing and logistics to pharmaceuticals, retail, and energy.
- Forecast sales.
- Product recommendations.
- Analyze assortment and so on.
- Customer analysis.
- Assortment analysis.
- Sales forecasts.
- Marketing and advertising budgets optimization.
- Supply chain management.
Logistics & Warehouses
- Travel management improvements.
- Warehouse optimization.
- Route management.
- Developing optimal loading systems.
- Improve preventive care.
- Create personalized treatments.
- Detect & analyze patient patterns.
- Bed management.
- Forecasting revenue.
- Optimizing production lines.
- Logistic chains management.
- Determining optimal employee workloads.
- Increase the yield of farmlands.
- Ensure serviceability of farm equipment.
- Monitor fields conditions
- irrigation, soil moisture, etc;
- predict weather conditions.