Getting more out of your data. LTG helps customers extract and visualize their data so they can make more informed business and IT decisions.
Machine Learning (ML)
Our data mining practice involves building data pipelines, data engineering and finally building a data warehouse. We understand there is more than one way to accomplish this and our consultants have a deep understanding of the leading techologies to help you choose the right tools for your particular needs.
Building and maintaining connections to various data sources requires a deep understanding of the data sources as well as the target business metrics.
Data Engineering is required to transform the raw data sources into consumable, often summarized, data that can be consumed by various reporting and visualization tools.
Where and how you store your transformed data is critical to how efficiently your algorithms or reporting tools can process the data. We can help you implement and architect your datastores to meet your security and scalability requiremnts.
LTG helps customers inspect, cleans, transform, and model their data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. Data analytics allows our customers to make more informed decisions and to stop guessing
By using visual elements like charts, graphs, and maps, LTG leverages data visualization tools to provide a more accessible way for our customers to see and understand trends, outliers, and patterns in data.
LTG builds on industry leading strategies and technologies to provide historical, current and predictive views of business operations. Business intelligence (BI) technologies enables us to handle large amounts of structured and sometimes unstructured data to help identify, develop and otherwise create new strategic business opportunities. Identifying new opportunities and implementing an effective strategy based on insights can provide our customers with more cost effective solutions and increased long-term stability.
Machine Learning (ML)
A method of data analysis that automates analytical model building. This branch of artificial intelligence is based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
Supervised Learning is a type of system in which both input and desired output data are provided. Input and output data are labelled for classification to provide a learning basis for future data processing. The learning process consists of three primary areas: hypothesize, error and train.