If a picture is worth a thousand words, but still missing valuable location data, then why not use artificial intelligence (AI) and machine learning (ML) to fill in the gaps? Take the image of Perth, Australia, below: This graphic below shows vast data sets containing buildings, green spaces, roads to travel, and parking lots. Drill […]
Case Study: Semantic Web Ontologies and Geoscience Collaboration Helps the Planet
In the geoscience community, collaboration is critical. Different disciplines — engineering geologists, geochemists, hydrologists — need to share their findings with each other to address big questions about the earth. Take climate change. What factors contribute to it? What impact will it have? Oceanographers who study the dynamics of oceans do their work individually […]
Data Governance and Data Science: What is the Intersection?
With the rising concern surrounding the manipulation of data and misuse of statistical methods in Data Science, it is becoming imperative that strong Data Governance policies and practices are put in place to curb any degeneration of data and the scientific methods used to arrive at data-driven conclusions. Data Governance (DG) is expected to play […]
Data Management vs. Data Virtualization
Data Management, as a principle, requires that data is brought to a single place, governed actively, and available in real time. It also includes the trust needed for business users to perform day-to-day business functions and to do it better than the competition. Data needs are contextual and based on the role of the user. […]
Data Modeling in the Machine Learning Era
Machine learning (ML) is empowering average business users with superior, automated tools to apply their domain knowledge to predictive analytics or customer profiling. The article What is Automated Machine Learning (AutoML)? discusses a prediction that by 2020, augmented analytics capabilities will play a key role and be a “dominant driver” in the growth (and purchase) […]
The Importance of Data Literacy
Walk into a company embracing digital transformation and you’ll find monitors displaying colorful charts and pie graphs decorated with numbers. These dashboards show information about the business meant to assist employees in prioritizing work, seeing new opportunities, and driving efficiency. An important question remains, though: “How many employees trained on a business’ dashboards know how […]
Machine Learning and Artificial Intelligence Trends in 2019
2019 will be a critical year for Artificial Intelligence (AI) and Machine Learning (ML) technologies as real-world industry applications demonstrate their hidden benefits and value to the consumers. So far, scientists and researchers have made claims on behalf of AI-enabled technologies, but they have not really been tested in large-scale market applications. We will see […]
Data Science Trends in 2019
When it comes to major Data Science trends to watch in 2019, the co-founder and CEO of Kaggle, Anthony Goldbloom, has predicted that very soon Data Centers will be replaced by departmental or business-specific Data Science teams. As discussed in Data Science Trends in 2018, last year’s major trends continued from 2017 as the growth […]
The Future of NLP in Data Science
According to many market statistics, data volume is doubling every two years, but in future this time span may get further reduced. The vast portion of this data (about 79 percent) is text data. Natural Language Processing (NLP) is the sub-branch of Data Science that attempts to extract insights from “text.” Thus, NLP is assuming […]
Business Intelligence and Analytics Trends 2019
In 2019, Advanced Analytics capabilities with minimal manual efforts will remain the hallmark of all competitive Business Intelligence solutions. The Business Application Research Center (BARC) 2018 Business Intelligence Survey indicates that the global BI solutions market is slated for major technological changes. The primary technology initiatives that BI users can expect in 2019 are Cloud BI deployments, BI […]