Data Journey – Overview
- Data is the new oil and an increasing number of organizations are focusing on reorienting their digitization strategy around data.
- Data drive digital initiatives and enterprise data has a typical journey all the way from sourcing to intelligent visualization.
- Choosing a custom solution in each of these phases will accelerate your digital journey and realize the power of new oil.
Data Journey – 4 Stages
A Data journey comprises four stages:
- Scraping or Aggregating Data
- Annotation or Data Labeling
- Leveraging Machine Learning & Artificial Intelligence
- Data Visualization
- Web scraping is a powerful data sourcing technique that leverages tools and frameworks to scrape data from the public domain.
- The scraped data can be aggregated and transformed into a meaningful format and loaded into any database in a structured format.
- Web scraping can be done using custom programming or by leveraging many tools.
- Web scraping is a powerful data extraction mechanism that will accelerate your data journey to annotate them for better grouping, build a cognitive intelligence layer on top of it using AI & ML, and leverage data visualization tools for better insights
- Labeling training data acts as the first step in the machine learning development cycle under Computer Vision.
- Consider we need to train a machine learning model to identify a specified category of objects from the collection of data.
- We would need to collect representation data samples which have to be classified and analysed along with a Machine Learning algorithm for handling each sample.
- Vision Analytics is used to train algorithms to analyze images and videos to detect and segment objects of interest and perform downstream analysis of the data
- Text analytics involves semantic analysis of text data like documents, email, webchat, social media, surveys, customer forums, etc. along with the process of building a searchable knowledge graph and insights.
- CONVERSATIONAL AI – Powerful AI engine trained on reams of data to understand customer needs. Chatbots can be trained to interpret and answer a wide range of questions for enhancing data accuracy, domain-specific and near human-like cognition.
- Data visualization helps in simplifying complex quantitative information into easily accessible representations such as graphs and charts.
- Data visualization is the final leg of the data journey where we aggregate data via scraping or ETL, annotate, build a cognitive intelligence layer, and enable tangible evidence via data visualization.
- The data visualization can be accomplished using open source frameworks or commercial platforms and we help you in picking the right tools based on use case fitment.