Blogs

Big Replicate: A big insurance policy for your big data

Big Replicate: A big insurance policy for your big data

April 18, 2017 | by Andrea Braida, Portfolio Marketing Manager, IBM
Dwaine Snow is a Global Big Data and Data Science Technical Sales Manager at IBM. He has worked for IBM for more than 20 years, focusing on relational databases, data warehousing, and the new world of big data analytics. He has written eight books and numerous articles on database management, and...
Analytics and the cloud: NoSQL databases

Analytics and the cloud: NoSQL databases

Schemaless databases and the role they play

April 6, 2017 | by Steven Lockwood, Executive Information Architect, IBM
Although NoSQL database technology has been around for a long time (before SQL actually), not until the advent of Web 2.0, when companies such as Google and Amazon began using the technology, did NoSQL’s popularity really take off. Market Research Media forecasts NoSQL Market to be $3.4 Billion by...
Incorporating machine learning in the data lake for robust business results

Incorporating machine learning in the data lake for robust business results

March 28, 2017 | by Karan Sachdeva, Sales Leader Big Data Analytics APAC, IBM
Building a data lake is one of the stepping stones towards data monetization use cases and many other advance revenue generating and competitive edge use cases. What are the building blocks of a “cognitive trusted data lake” enabled by machine learning and data science?
Charting the data lake: Using the data models with schema-on-read and schema-on-write

Charting the data lake: Using the data models with schema-on-read and schema-on-write

March 14, 2017 | by Pat O'Sullivan, Senior Technical Staff Member, IBM Analytics
In many cases the data lake can be defined as a super set of repositories of data that includes the traditional data warehouse, complete with traditional relational technology. One significant example of the different components in this broader data lake, is in terms of different approaches to the...
Analytics and the cloud: The Internet of Things

Analytics and the cloud: The Internet of Things

Managing the growth of a connected world to gain new insights

March 7, 2017 | by Steven Lockwood, Executive Information Architect, IBM
This is the second in a series of blogs on analytics and the cloud. We will consider the rise of the Internet of Things (IoT), analytics used on that data and how the cloud can be utilized to drive value out of instrumenting a very wide range of ‘things’.
Fundamentals for sure-fire cloud data warehouse optimization

Fundamentals for sure-fire cloud data warehouse optimization

An interview with James Kobielus

March 2, 2017 | by Andrea Braida, Portfolio Marketing Manager, IBM
There is a growing need for versatile, hybrid architectures that can combine the best of both data warehousing and big data analytics. The cloud is the perfect solution, because it makes it easier to build a robust data warehouse as a central “hub”, and then add other environments that can be...
Analytics and the cloud: A perfect match

Analytics and the cloud: A perfect match

February 7, 2017 | by Steven Lockwood, Executive Information Architect, IBM
This is the first in a sequence of blogs that takes a peek at what is driving analytics onto the cloud, what are the challenges that will need to be overcome over the next 5 years and how they will be tackled.

5 key attributes of effective data monetization strategy

February 6, 2017 | by Karan Sachdeva, Sales Leader Big Data Analytics APAC, IBM
In cognitive computing era, new revenue generation stream has emerged with data at center of the modern digital business model. One of the key capabilities cognitive computing enables for an organization is the ability to generate additional revenue streams by using data effectively. In the big...
IBM’s big data meetup program approaches a significant milestone

IBM’s big data meetup program approaches a significant milestone

February 3, 2017 | by Nancy Berlin, WW Event Manager, Analytics Platform Services, IBM
IBM’s community of big data developers continues to grow. As our Big Data Developer meetup program moves into its fifth year, this worldwide community of customers, partners and IBM developers is on the verge of enlisting its 100,000th member—when we published this blog, we counted 99,100. 
Stream processing and the IBM Open Platform

Stream processing and the IBM Open Platform

Choosing the right engine for real-time data processing with Hadoop

January 27, 2017 | by Andrea Braida, Portfolio Marketing Manager, IBM
Analyzing streams of big data in real time can have a big impact on competitive advantage. In a world of bewildering stream processing engine choices, explore the use-case-dependent alternatives that can provide well-suited business outcomes, courtesy of expertise from Roger Rea and Jacques Roy.

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