Posts Tagged ‘Big Data’

Recently, the news broke that Optimizely acquired Netspring, a warehouse-native analytics platform. I’ll admit, I hadn’t heard of Netspring before, but after taking a closer look at their website and capabilities, it became clear why Optimizely made this strategic move. Simplifying Omnichannel Analytics for Real Digital Impact Netspring is not just another analytics platform. It […]

For my first time attending the International Manufacturing Technology Show (IMTS), I must say it did not disappoint. This incredible event in Chicago happens every two years and is massive in size, taking up every main hall in McCormick Place. It was a combination of technology showcases, featuring everything from robotics to AI and smart […]

The Hadoop Ecosystem Hadoop Ecosystem is a platform or a suite that provides various services to solve big data problems. It includes Apache projects and various commercial tools and solutions. 4 major elements of Hadoop are HDFS, MapReduce, YARN, and Hadoop Common. Hadoop is a framework that enables the processing of large data sets which […]

Have you ever wondered if it would ever be possible to time travel like in the old movies with a time machine? If we could go back in time and see the world, would we? If you asked me, I would have said yes! But not in the way that Hollywood portrays science fiction films. […]

The Data and AI Summit 2022 had enormous announcements for the Databricks Lakehouse platform. Among these, there were several exhilarating enhancements to Databricks Workflows, the fully managed orchestration service that is deeply integrated with the Databricks Lakehouse Platform and Delta Live tables too. With these new efficacies, Workflows enables data engineers, data scientists and analysts […]

Snowflake is Cloud hosted relational database used to create Datawarehouse on demand. Data in the data warehouse can be loaded as full load or incremental load. The full load is a process of deleting whole existing data and reloading it again. Full loads are time and resource-consuming tasks compared to incremental loads that only load […]

The stakes to evolve your business and adapt to new realities have never been higher. How do you accelerate and scale your transformation cost-effectively? The answer – optimized global delivery. Follow this series and learn more about our nearshore software development capabilities from members of our global consulting team in Colombia. When coordinating software development […]

COVID-19 has undoubtedly affected financial services trends in 2020 and will continue to do so into 2021. Since the pandemic began, financial services organizations have been responding to the crisis with continuity plans to address everything from bankruptcies to people losing their jobs and ability to pay their bills on time. Now more than ever […]

The COVID-19 pandemic has done a great job revealing trouble spots and gaps in many companies’ technology strategies this year. If you’ve discovered that your data strategy and technology solutions need improvement, then this podcast is for you. Join host Arvind Murali, Principal and Chief Strategist of Data at Perficient, for the first season of […]

Big Data is one of the most valuable commodities in business today, but only if organizations have the power to analyze it and make it work for them. The term “Big Data” represents a massive amount of structured and unstructured data from several different sources. As more and more companies find themselves in possession of […]

Recently, Perficient’s Scott Albahary, Chief Strategist of Financial Services, and Arvind Murali, Chief Strategist of Data Governance, presented a webinar that discussed what it takes for banks and insurance companies to acquire and retain customers. The key, they say, is to create a 360-degree view of customers. Without a holistic view, a company can never […]

First a quick summary of machine learning (ML).  At a high level and simplifying a bit, there are basically two types of ML: Supervised learning – a labeled data set is used to train an ML model to make predictions. The ‘trained’ ML model is then applied against a data set to make the predictions […]