In this special technology white paper, The 5 Key Challenges to Building a Successful Data Science Lab & Data Team, you’ll learn how a Data Lab establishes an effort to answer business needs by making sense of raw information. Data labs are intended to create critical mass within the organization that enables them to reach the level of innovation required for new data-driven products.
This is the third article in a series focusing on a technology that is rising in importance to enterprise use of big data – IoT Analytics, or the analytical component of the Internet-of-Things. In this segment, we’ll provide an overview of the rise of IoT analytics. IoT Analytics implies data, fast data, and big data. IoT is not just about capturing sensor data, or GPS locations, or temperature, or velocity changes. You have to find meaning in that data through analytics.
In this special technology white paper, From Development to Production Guide – Finding the Common Ground in 9 Steps, you’ll learn how managing a successful data science project requires time, effort, and a great deal of planning. Defining the problems to solve and planning the project’s scope is just the tip of the iceberg, as team members need to fully understand all aspects of a project in order to effectively contribute.
In this contributed article, Jerome Ternynck, CEO at SmartRecruiters discusses the impact AI and machine learning are having with day-to-day processes for talent acquisition teams. His company recently hosted a Hiring Success meetup and invited recruiting industry experts to share their thoughts on the future of AI and talent acquisition. Here are some of the overarching themes that came out of the event.
Contributed by Daniel D. Gutierrez, Managing Editor of insideBIGDATA, this is the first article in a series focusing on a technology that is rising in importance to enterprise use of big data – IoT Analytics, or the analytical component of the Internet-of-Things. In this first segment, we’ll set the stage for our discussion by providing an overview of the Internet-of-Things. The Internet of Things (IoT) is an emerging theme with wide technical, social, and economic significance. Consumer products, durable goods, automobiles, industrial equipment, utilities, various sensors, and other everyday devices are being combined with Internet connectivity and powerful analytics capabilities that promise to be transformative in terms of the way we live, work, and play.
In this special feature, Steve Wilkes, co-founder and CTO at Striim, Inc. the real-time data integration and streaming analytics platform, offers his top predictions for 2017 on how real-time data integration and streaming analytics will impact the many areas it touches, including Cloud, IoT, Integration, Analytics, Big Data and Security.
In this contributed article, technology writer and blogger Kayla Matthews discusses how big data can be used to fight infectious disease threats.
I recently caught up with Natalia Hernandez, Data Scientist at Foodpairing, to highlight how her company’s data scientists mine public online data, which gives general trend insights to use consumer intelligence and molecular analysis of ingredients to forecast the next big flavors in the food industry.
Wow! What a year 2016 has been. The big data industry has significant inertia moving into 2017. In order to give our valued readers a pulse on important new trends leading into next year, we here at insideBIGDATA heard from all our friends across the vendor ecosystem to get their insights, reflections and predictions for what may be coming. We were very encouraged to hear such exciting perspectives. Even if only half actually come true, Big Data in the next year is destined to be quite an exciting ride. Enjoy!
Industry’s Most Comprehensive Big Data Maturity Survey Reveals Surprising State of Hadoop, Dramatic Rise of Big Data in the Cloud
AtScale, the company that provides enterprises with a fast and secure self-service analytics platform for Big Data, announced the results of the 2016 Big Data Maturity Survey. Based on 2,550+ responses from big data professionals at 1,400 companies across 77 countries, the report reveals new & unexpected insights about Cloud, Big Data, Business Intelligence, Hadoop and Spark.