Typically, ingesting streaming event data, persisting with low latency and analyzing it along with historical event data requires integrating multiple analytic systems. IBM EventStore is purpose built to simplify the complexity of harnessing event data with a single system. Its unique architecture
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?
On June 13th 2017, Hortonworks and IBM announced an extension of our partnership. A key part of this partnership is the collaboration on IBM Data Science Experience (DSX). This collaboration is win-win in that it brings a production-ready full-cycle data science experience to Hortonworks Data
Universal connectivity is fueling streams of event data from a variety of event sources. Increasingly, organizations are developing and deploying event driven applications to harness the growing volumes of event data. IBM EventStore offers a scalable integrated system for enterprises to ingest,
In the connected world of today’s digital economy, apps, IoT devices, vehicles, appliances and servers are generating endless stream of event data. The stream of events describes what is happening over time and offers the opportunity to track and analyze things as they happen.
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
Today, data is the most valuable resource of any business, enabling the actions and insights that empower business disruption. But it can only do so if it’s fully liberated to work for you. We’re working towards a future in which businesses can unleash the power of their databases without
If you’re truly data-driven, how often do you make a critical decision based solely on information from one part of the company? At the organizational level, how valuable is data when decision makers have to rely on IT (not to mention a tangle of technical and bureaucratic red tape) just to access
Upon reading his own obituary in the newspaper, famed author Mark Twain is said to have remarked that reports of his death were greatly exaggerated. I can only imagine that if the data warehouse appliance were a 19th century American novelist, it might say the same thing. For a while now,
If you joined us or tuned in for IBM’s Fast Track Your Data broadcast from Munich last week, you heard us talk about the history of cars – a most appropriate location for the discussion. But it wasn’t until Henry Ford and the assembly line over twenty years later that the automobile was advanced
One of the hallmarks of the cognitive era of business is that companies can can be positioned to unlock insights from unprecedented volumes of data. Advancements in cognitive computing and artificial intelligence (AI) might hold the most significant opportunity where companies can win with data-
A decade ago, governance was dictated and enacted by a select group of people. Today, while the principles of governance are largely owned by the same select group of people, everyone has a hand and shared responsibility in the enactment and fulfillment of governance.
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.
No matter what site you search, it’s pretty clear that self service data is a top trend in the data market today. The knowledge and insight that we can obtain from data is truly a secret weapon. But the challenge is making the data available while keeping it trusted and governed.
Recently, I had the honor of speaking with a number of the world’s most influential thought-leaders in the fields of data science, data analytics, machine learning and digital transformation. This group of prominent data technologists was more than happy to answer a wide variety of question on