Reinvent your core workflows with technology and unlock intelligent value across various business functions

Incorporate Data Science into your core business processes and make your processes and applications better...and smarter

You understand that having a data-driven culture is important for your business. We help businesses like yours learn how to fluently speak data science and integrate it into your daily operations. Our mission is to help our clients extract valuable business insights from their data to better understand their audience, forecast demand, reduce risks, prevent cost overruns, and much more.

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TIU’S Data Science Process

Business Understanding

The “Business Understanding” phase requires getting to know your business. We’ll start by asking relevant, meaningful questions so we can define objectives for the problem that needs to be tackled.Then we begin the data acquisition phase that will include intensive back and forth
discussions with the SMEs (Subject Matter Experts), or domain experts to identify the kind of datasets needed for the business use-case.We use a set of standardized processes to collect data from your business. If required, we can scrap the data by doing market research. We do take advantage of open-source datasets to kick start the model learning.

Data Preparation and Cleaning

Before training our models, we need to develop a sound understanding of the data. Real-world data sets are often noisy, with missing values, or may have a host of other discrepancies.We work with a set of processes that are designed to audit the quality of our datasets, and provide the information you needed to prepare for the modelling phase. This process is often iterative.

If necessary, we may set up a process to score new data or refresh the data regularly as part of an ongoing learning process. Scoring may be completed with a data pipeline or workflow.

Data Exploration and Understanding
Once our team is satisfied with the quality of the cleansed data, the next step is to better understand the patterns that are inherent in the data. Data analysis helps us to choose and develop an appropriate predictive model for your specific business needs. Using a variety of visualizations can help us find many answers and develop hypotheses before modeling.


Feature Engineering

Feature engineering involves the inclusion, aggregation, and transformation of raw variables to create the features used in the analysis. We’ll select important features, and construct more meaningful ones using the raw data provided. It's critical to understand what is driving a model, which gives us an idea of how the machine-learning algorithms can use those features.

Model Training/Evaluation/Tuning

Here we will train machine learning models, evaluate their performance, and use them to make predictions. Depending on the type of data query your business is working on, there are many modeling algorithms available. Our team of expert data scientists can help find what your business is looking for.

Data Deployment

Here we deploy models with a data pipeline to a production or production-like environment for final user acceptance. Depending on the business requirements, predictions will be made either in real-time or on a batch basis.To deploy models, we expose them with an open API interface. The interface enables the model to be easily consumed from various applications, such as:

  • Websites
  • Dashboards
  • Line-of-business applications
  • Back-end applications
  • Mobile Applications
Customer Acceptance and Hand-off

TIU has a very smooth hand-off process, where our team prepares detailed project documentation with all the experiments that we've performed, which may include failed experiments as well. We communicate these findings with key stakeholders, and confirm that the deployed model and pipeline meet the customer's needs. At this point we hand the project off to the entity that's going to run the system in production.

Services We Offer

  • Cognitive Document (CDP)Services
  • Smart Assistants (Chat-Bots)
  • Descriptive, Predictive, Prescriptive and Compartive Analysis/Maintenance
  • Time Series Forecasting
  • NLP( Natural Language Processing + Model Building + Sentiment and Text Analysis + Subjective Analysis)
  • Social Media Mining
    • Conjoint Analysis for Market Research
  • Deep Learning
  • Face Recognition and Image Processing (Yes, This comes under Data science, By having the knowledge of building Predictive models combined with Nueral network, AI and ML)
  • Cognitive Learning (Pattern Recognition, NLP, AI and ML)
  • Behavioural and Statistical analysis. (Specially used by Tax and Accounting Firms on Financial Data)

If you are looking for a reliable technology partner to create innovative, market-leading solutions for your business, we are here to help! Request a free consultation today and let’s get started on your AI or Data Science project today.

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US Offices

Cleveland Office:
2000 Auburn Drive
Suite 200
Beachwood, OHIO 44122

Phone: 800-578-1904
Fax: 866-691-8620

Hudson Office:
118 W Streetsboro
Suite 183,
Hudson OH 44236

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