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Learn how the IBM Integrated Analytics System, a unified data platform built on the IBM Common SQL Engine, helps do data science faster with high performance, embedded machine learning capabilities and built-in tools for data scientists to deliver analytics critical to increasing your organization’
Data already is the new currency and is at the heart of everything digital. I like to repeat the adage, “Data becomes Information, becomes Knowledge, becomes Wisdom”. And “It’s all about the data”. So why do we send up probes, sensors or satellites — for the data?
The latest executive report published by IBM Institute for Business Value puts the estimated cost of cyber crime to the global economy in a range of USD 375–575 billion per year. Reputational damage, which is hard to calculate, comes on top of all this. No industry and geography has remained
It seems that we’re reaching the point where the Internet of Things (IoT) is moving from the domain of enthusiastic early-adopters to the more challenging, more profitable territory of mainstream enterprise technology. Event-driven architectures are playing a key role in these types of applications
If you read a lot of development blogs nowadays, you’ll probably notice a common theme: developers don’t want to deal with databases. They want to focus on designing, building, testing, and deploying applications that deliver value to the business as quickly as possible.
Big data isn’t just getting bigger. It’s getting more valuable. As companies work to unlock more value from their data, one of the biggest challenges to address is disconnected data silos. Big companies don’t have one data lake, they have data lakes, ponds and pools.
Data, insights, cloud, agile, analytics. These are all terms that get thrown around a lot in technology these days. But the truth is that unless you can combine some or all of these concepts, the bottom line benefit to your business will likely not as great as you may expect.
This is the fourth in a series of blogs on analytics and the cloud. Read our introduction to the series. This blog concerns itself with the rise of open source software and how it is used for a whole host of analytical purposes. However, as will be seen in this blog, there are significant gaps in
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
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’.
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.
Today’s businesses need a culture of collaboration that empowers knowledge workers to glean cognitive insights from data that help transform and modernize operations. See how cloud-based platforms and solutions enable data scientists and other experts to exploit artificial intelligence, machine