Data Analytics


Data Analytics


Vista provides data analytic services and solutions using the latest industry standard frameworks. Our activities range from data engineering services such as data model design, cleaning, restructuring, ETL, and online/offline analysis pipelines to data insight services based on statistical analysis, machine learning, and artificial intelligence. Our team has extensive experience working with large databases and data warehouses using the latest cutting edge, industry standard big data frameworks.
Our integrated platform allows us to deliver insight for our clients. Combined with our analytics pipeline capabilities, our clients are provided with a range of services, from ad-hoc to fully online reports, and gain meaningful and valuable insights into their operations.

Core Analytics

  • DescriptiveWhat has happened and is happening?
  • PrescriptiveFind the best course of action for a given problem.
  • ExploratoryWhat hidden information exist in data?
  • Predictive What will happen in the future.

We use SUMIT framework for analyzing data which helps us to:

  • Reusable and modular analyzing components
  • Streaming analysis and visualization
  • Notifications to identify anomalies
  • Big data analysis on commodity hardware

We also use appropriate statistical methodologies for data analysis modeling

Machine Learning Algorithms

Classification, Clustering Models

Time Series Analysis

Summarization and Data Visualization

Regression, Correlation Analysis

Principle Component Analysis

We have these roles in Vista data analytics team:

Data Analyst

Deliver value by taking data, using it to answer questions, and communicate the results to help make business decisions.

Data Engineer

Build and optimize the systems that allow data scientist and analysts to perform their work.

Data Scientist

Discover hidden insights in data by leveraging supervised and unsupervised machine learning models.

How Vista data science services works:

  • Understand the needs of your business
  • Construct measures to support business decision-making
  • Capture data in transactional systems to allow tracking of measures
  • Engineer data for regular reporting and analytics
  • Conduct analysis to address business questions
  • Translate analysis for the business with visualization techniques