Privacy-Preserving Data Sharing for Data Science

Privacy-Preserving Data Sharing for Data Science

  • Posted by Daitan Innovation Team
  • On April 15, 2020
  • Artificial Intelligence, Data, Data Science, Data Sharing, Deep Learning, Differential Privacy, Privacy
In the last 2 decades, with the increasing availability of sensors and the popularity of the internet, data has never been so ubiquitous. Yet, having access to personal data to perform statistical analysis is hard. In fact, that is one of the main reasons we, as data analysts, spend so much time doing research using “toy” datasets, instead of using real-world data.
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 Programming With Data

Programming With Data

  • Posted by Daitan CTO
  • On November 5, 2019
  • Data, Data Centers, Data Science, Machine Learning
In this post, I will share a very basic view of the technologies that are used to build ML solutions with the goal of helping those who have not had exposure to this domain understand where all the hype comes from. For my engineering colleagues, keep in mind that this article is meant to very simply present this technically complex field; and, does not tackle detailed technical challenges, the compelling issue of bias, and social concerns about ML/AI replacing jobs.
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 Fundamentals of Time Series Data and Forecasting

Fundamentals of Time Series Data and Forecasting

  • Posted by Daitan Innovation Team
  • On July 25, 2019
  • AI, Data, Time Series Data, Time Series Forecast
Time series forecasting is the use of statistical methods to predict future behavior based on historical data. This is similar to other statistical learning approaches, such as supervised or unsupervised learning. However, time series forecasting has many nuances that make it different from regular machine learning. From data processing all the way to model validation, time series forecasting is a different beast.Many companies are exploring time series forecasting as a way of making better business decisions.
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 Data Pipeline & Analytics Solution

Data Pipeline & Analytics Solution

  • Posted by Wilker Amorim
  • On December 7, 2018
  • Analytics, Data, Telecommunications
Building a near real-time analytics system, orchestrating multiple computer clusters analyzing over 15 billion events (or 13 Terabytes of data) per day.
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 An AI-Powered Customer Experience Requires Breaking Down Data Silos

An AI-Powered Customer Experience Requires Breaking Down Data Silos

  • Posted by Marketing Daitan
  • On September 6, 2018
  • AI, Architecture, Customer Experience, Data
BLOG - Today’s consumer expectations cannot be ignored. A customer calling a company on their mobile phone, texting via a message window, or emailing to a support system, expects that company to know instantly who they are without asking
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 Practical Facts About the Current State of Machine Learning and Artificial Intelligence

Practical Facts About the Current State of Machine Learning and Artificial Intelligence

  • Posted by Marketing Daitan
  • On August 11, 2018
  • AI, Data, Digital Transformation, Machine Learning
Over the past 2 years, Daitan has helped a number of our clients implement advanced technology solutions, as well as provided Data Science, Data Engineering, Customer Experience and DevOps resources to successfully implement it. In our experience, companies are taking measured steps to take advantage of Machine Learning and Artificial Intelligence technologies based on clear business objectives that intelligently further growth.
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 An AI-Powered Customer Experience Requires Breaking Down Data Silos

An AI-Powered Customer Experience Requires Breaking Down Data Silos

  • Posted by Marketing Daitan
  • On June 11, 2018
  • AI, Customer Experience, Data
Today’s consumer expectations cannot be ignored. Gartner predicted that by 2020 customers will manage 85% of their relationship with an enterprise without interacting with a human. The convergence of data, devices and technologies like Artificial Intelligence are making the vision a plausible outcome for businesses pursuing Digital Transformation.
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 The Shift from Data-Centric to Event-Centric Thinking Underscores Digital Business Transformation

The Shift from Data-Centric to Event-Centric Thinking Underscores Digital Business Transformation

  • Posted by Marketing Daitan
  • On March 4, 2018
  • Architecture, Data, Event-Driven Architecture
One of the better outcomes of Digital Business has been that organizations are becoming outward-facing and more inclusive of their customers’ needs, reactions and feedback. As a consequence, their customer facing solutions are transforming into fully inclusive, engagement-driven ecosystems. This shift is driving a transition from retrospective data-centric thinking to event-centric thinking. Gartner comments in their May 2017 report, Champion Event Thinking to Excel at Digital Business:
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