A master data management (MDM) strategy can help businesses make intelligent business decisions and avoid unnecessary expenses while enabling efficient deployment and saving time spent on implementation. Discover the four essential capabilities of a strong MDM solution and how they can help you
So you want to enter the data science field, or maybe you are already a data scientist looking to expand your horizons. Several routes into the profession can provide the core skills, knowledge and best practices necessary to become a developer in the era of cognitive computing. And events such as
Apache Spark is exploding as a worldwide phenomenon since its origin in the Silicon Valley area of California. Find out just who widespread its adoption has grown in a survey of global examples, a wide array of community participations and upcoming event opportunities.
Find out how Day 3 of the conference offered insight into how data scientists have benefited from the latest approaches to web-scale analytics, including open sourcing of the System ML machine learning library to help the Spark community.
Attendees on Day 2 of Strata + Hadoop World were treated to a range of speakers from various industries, as well as important keynotes and interviews that focused on critical data-related topics. Read about these and other highlights from that day's sessions.
The idea that data-at-rest (historical) and data-in-motion (immediate) are mutually exclusive no longer applies, thanks to a new toolset that handles both. Discover how organizations can have it all: the ability to stream data in real time as well as process historical data to highlight patterns in
As a strategic sponsor, IBM was represented in full force at Strata + Hadoop World 2015 in New York, New York. Day one proved to be a buzz of activity that included IBM data science experts getting a hands-on lab course on practical data science underway, IBM spokespeople discussing offerings and
Choose a solution that can deliver deep insights into data without reinventing the wheel. Standardization can help you move large quantities of data across multiple systems, allowing you to take advantage of data no matter its source.
What are your big data requirements? Determine which type of Apache Hadoop user you fit most closely. Take a short quiz to see what kind of Hadoop user you likely are and what you likely need from Hadoop to be successful.
Data scientists may be of a different breed from other analytics team members, but they are essential for bringing to the table curiosity about data and an unquenchable thirst for finding patterns and relationships in that data. Discover how combining the roles of data scientist, business analyst,
Big data has shown itself to be an illuminating force for sourcing the insight that is powering a tremendous transformation in modern life. To keep pace with the rapid changes, today’s organizations are seeking to improve their capabilities, competencies and culture to turn data into business value
Why are people talking about Apache Spark? It’s because many organizations are using the myriad features of this open source engine to boost their predictive analytics processing. The result? Better, deeper and faster data analyses with reduced coding time and effort.
Hadoop is great for storing and processing large data volumes, but its limits become clear when integrating ever-increasing volumes of data. A new solution—described in detail at the upcoming Strata+Hadoop World conference—can help organizations overcome this limitation.