Posts Tagged ‘Big Data’

I implement distributed persistence solutions for enterprises. For use cases involving highly-available, low latency processing, I typically use DataStax Enterprise. Apache Cassandra provides great persistence characteristics for a real-time, distributed transactional store. For real-time stream processing, I’m a Spark fan. Throw in Solr and graph, add in operational support, and I have all of my […]

I implement distributed persistence solutions for enterprises. For use cases involving highly-available, low latency processing, I typically use DataStax Enterprise. Apache Cassandra provides great persistence characteristics for a real-time, distributed transactional store. For real-time stream processing, I’m a Spark fan. Throw in Solr and graph, add in operational support, and I have all of my […]

Big Data Analytics Platforms continue to be adopted by different organizations to get unique insights for their business. In this post, I will cover five common use cases that we are seeing with our customers who are adopting Big Data for their Business Analytics need. 1 ) Data Warehouse Modernization As organizations look to modernize their […]

I was reading an article about “Amazon using its MultiDimensional Datasets”. The news never gets old to me that Amazon Retail leveraging its Big Data Ecosystem to access 1,000,000,000 GB of data on more than 1,400,000 servers to increase sales through predictive analytics does personalized recommendations, price optimization, and anticipatory predictions on what the customer […]

In the world of Big Data, Data engineers always strive to find a way or method to analyze, process, and compute the Volume, Velocity, and Variety of data, and to provide Data scientists with a resilient backbone to conduct their analysis. Before the introduction of the cloud platforms, all the big data processing and managing […]

Romantics and poets have spent considerable amounts of time trying to quantify love over the past several centuries with very limited success. Scientists including Johannes Kepler (more famous for discovering law of planetary motion) even devised the Marriage (Secretary) Problem, a method using interviewing methods and analytics for increasing optimizing finding a mate. More recently, […]

Most of the time as a data scientist I get asked the question, what is the difference between Machine Learning and Statistical Learning? Even though you would think that the answer is obvious, there are a lot of novice data scientists that are still confused about those two approaches. As a beginner data scientist, it […]

New year, new resolution. This should apply to both person and business. 2017 was disruptive yet progressive for tech and digital marketing in many ways. We witnessed surge of AI and machine learning, emerging technologies like voice, facial recognition, virtual reality, augmented reality were built into many hit products/applications, holiday season had record breaking online […]

New Year – new data compliance. As analytics and big data continue to gain acceptance in the enterprise, governments are catching on and developing regulations to curtail abuse and monitor responses to data breaches. In particular, organizations doing business in Europe will need to comply with The General Data Protection Regulation (GDPR), set to go […]

It is no secret that a data science and analytics specialty was one of the hottest and fastest growing careers in 2017, leading to resource shortages (as denoted by the picture below). However, in 2018 and beyond, a data scientist will evolve into data engineer, a data steward, and a governance lead. Every field will […]

In healthcare, most data is exchanged electronically between partners via EDI (Electronic Data Interchange), and “Big Data” is helping the industry become more efficient and productive. EDI originated because it provided a structured mechanism for sharing data between disparate organizations and systems. The more common means of transferring data from source to a data warehouse […]

Bigdata is generally a lot of data produced very quickly in many different forms. Data might include customer transactional histories, production databases, web traffic logs, online videos, social media interactions, and so forth. The challenge for Data Management can be coined by three V’s” – “volume, velocity and variety. Big Data is special because it […]