When the data lake is deployed as an infrastructure to be exploited by different users in various departments with their own needs, their own different requirements and often their own dialects in terms of a business language, then a universal translator can become very useful. Especially with the
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.
It is said that more data has been created in the past two years than in the entire preceding history of mankind. It would be interesting to find out how much of this data has been analyzed and put to good use. Analyzing and harnessing big data is undoubtedly the major challenge of the day for all
Elderly care is on tap to be a critical need in the coming decades. See how Caregivers.com is using cloud computing and mobile technologies to provide greater choice for families and higher wages for in-home caregivers.
The unprecedented evolution of social media data’s influence on business can have tremendous impact on how customers are integrated into organizational goals and practices. See why more organizations than ever are using social media data to take a customer-centric approach to evolving their
Data models for developing data warehouses need to evolve for managing and defining data lakes. This first installment of a blog series on charting the data lake introduces the potential role of data models in data lake environments and how they need to take an active role in defining and managing
Data transformation doesn’t have to mean moving data away from its source. Rather, modern approaches to data transformation offer a range of advantages that can help enhance performance while heightening access to data.
Ever hear of the Big Data Dudes? If not, crawl out from under that rock and see what these intrepid big data and analytics heroes are up to in their latest analytics blockbuster, "Big Data Dudes and the Lost in Las Vegas Mystery."
The concept of big data fabric represents a fundamental change in how businesses approach data storage, fast data analytics, and streaming data to make it much easier, faster, and simpler to retrieve actionable information and increase the value that you can get from customer data.
Emerging technologies—3D printing, cloud computing, the Internet of Things, mobile computing, sensors, wearable devices and the like—are transforming the ways in which modern organizations manage and use data. But much of that data remains unused. Successfully capitalizing on information
We are excited to announce the GA of the BigInsights for Apache Hadoop Basic plan on Bluemix! Over the last three months, the service has been available as a public beta. It was encouraging to see the participation and feedback during the beta. The feedback has been valuable in improving the
The Internet of Things continues to be a land of opportunity in so many areas. Take a look at this overview of steps to innovation and success factors along with the risks and pitfalls to avoid in your Internet of Things journey.
Why has IBM created its own distribution of Apache Hadoop and Apache Spark, and what makes it stand out from the competition? We asked Prasad Pandit, program director, product management, Hadoop and open analytics systems, at IBM to give us a tour of the reference architecture for IBM Open Platform
Many of us might be surprised to learn that some of the most familiar brand names around started off with other names. IBM recently renamed IBM DataWorks—its flagship, self-service data preparation offering—to IBM Bluemix Data Connect. Get a glimpse of it in this brief overview, and discover how
The inability of lines of business to not serve requests because they have to wait for IT provisioning can lead to a proliferation of analytics silos that can cause a loss of control of data. See how the next big stage of analytics with integrated Apache Spark helps organizations understand the