Big Data / Analytics
MySQL began as a company-owned open source project to deliver low cost, easy to manage RDBMS technology to the masses. Today, there is a wide variety of companies offering complementary technologies, and more than a few offering variant distributions based on MySQL. All these are celebrated at Percona Live!, the MySQL user conference sponsored by a company that offers one of those variant distributions, but also supported by its competitors, including Oracle. At this year’s conference in San Jose, California, this analyst focused on two products offering variant MySQL technologies aimed at the analytic-transaction processing (ATP) space; DeepSQL and MemSQL.
MySQLbegan as an open source product with a “free” community version and an “enterprise” version that required a subscription. It gained broad adoption very quickly, especially among those developing Web based applications on large server farms, who simply could not afford the licensing fees, generally priced by processors or cores, that attended most commercial RDBMS products. After the owning company, MySQL AB, was acquired by Sun Microsystems, and Sun was acquired by Oracle…
A new kind of database query processing technology is emerging: one based on graphics processing units (GPUs). Unlike conventional technology that limits its processing to CPUs, these new products can crunch large sets of numbers in parallel in a fraction of the time that the same queries require on regular systems. This is because GPUs, which were originally developed to perform the calculations necessary to drive real-time graphics, can concentrate terrific processing power on many problems simultaneously. GPU databases promise to be a key to handling very complex queries, where answers are needed to drive ongoing processing in an increasingly dynamic, stream-driven, smart processing environment.
Since the first database was created in the 1960s, database technology has evolved to provide better support for complex queries. They pose tough challenges, because in addition to requiring the collection of data from all over the database, many calculations must be made, preferably in parallel. Decades ago, we accepted that such queries could run a long time; we would submit them in batch and hope they didn't time out during the 6 hour overnight batch window. Then came symmetrical…
As the market for intelligent applications and the software platforms used to build them has emerged over the last few years, there has been a lot of nomenclature confusion. What should we call these applications and what should we call the platforms, libraries and software tools used to build them?
The terminology matters. It should matter for vendors looking to differentiate their products from the business intelligence and predictive analytics software that has existing for decades. 'Intelligent applications' and 'business intelligence' software provide two very different sets of functionality. It should also matter to technology buyers, who need to explain and justify new solutions to those holding budget.
We could use the name of the types of algorithms to describe the platforms;…
......Given that we do not yet have a separate community for Digital Strategy-related topics, I thought that the Analytics and Big Data community would be good place to post this one. Here's the premise - Analytics and big data lead to better business insights around customers, operations, and products and services. Insights in turn define and defend corporate strategies in the digital era, and well executed strategies lead effective digital transformation. See if you agree.
Over the past twelve to eighteen months the business consulting industry has introduced a new lineup of digital services positioned to help clients accelerate successful digital risk taking and maximize value of digital enterprise strategies. New digital offerings from the largest, multi-national and technology-focused business consulting firms have come to market through acquisitions of smaller digital-led firms, by re-orientating traditional strategy, consulting, and tech/ops engagement…
Informatica announced an agreement on April 7 2015, to be acquired by Permira Funds partnered with Canada Pension Plan Investment Board. This article provides some of the details and speculates on why we are seeing a trend of public technology companies going private.
Data, whether big or little, is a hot topic that goes beyond the bits and bytes that make it up. Data is at the core of business operations, strategic planning, execution and outcome. Getting data from the bits and bytes to the business level requires functionality to profile, cleanse, integrate, secure and analyze relationships in and through it. Informatica, one of the leading pure play data management software vendors able to deliver these types of solutions, has agreed to cleanse,…
I recently completed an IDC MarketScape on Decision Management Software Platforms. This research project gave me the opportunity to speak to several vendors in the market including, FICO, IBM, Oracle, SAS and TIBCO, several of their customers who adopted the solutions, and put the findings in the context of the decision management research I have been doing for many years. Until this platform market emerged a few years ago, customers cobbled together rules engines, advanced analytic tools, interfaces and alerting capabilities to develop decision management solutions. These solutions used rules to enforce resource constraints or maintain compliance with external regulations and internal policies while applying predictive analytic models to generate optimal decision choices. These decision options could be automated if an event met acceptable confidence thresholds or served to front-line employees who could then take action based on recommendations.
The rise of Internet connected devices presents opportunities to harvest the data and leverage it for new types of intelligent applications and services. This post reviews some of the factors impacting demand and supply of a new wave of analytic applications.
Predictive Maintenance Applications and Services
In a recent visit to Mexico City for an IDC Big Data and Analytics conference , I spoke to a CIO from a large mining company. The maintenance of the equipment used in mining operations is a high value process. Unless the drilling equipment is functioning, mining operations stop. Given the distributed, remote sites where the mining is conducted, an unplanned failure of operational equipment can take days to repair, and can lead to millions…
A newly published IDC multiclient study discusses the best practices and strategies to unlock the hidden value of information. Research from IDC shows that unstructured content accounts for 90% of all digital information. This content is locked in a variety of formats, locations, and applications made up of separate repositories. When connected and used properly, such information typically can help increase revenue, reduce costs, respond to customer needs more quickly and accurately, or bring products to market faster.
A major pharmaceutical manufacturer generated millions of dollars in new revenue by combining new research with previous research and drug studies. A global investment bank is generating significant new revenue, in part, thanks to a new knowledge management system, collecting, locating, sharing, synthesizing, and analyzing information across the globe about financial and investment topics collected from a wide variety of sources. These are just two examples from organizations I and my IDC…
Twitter's purchase of Bluefin Labs in 2013 and Gnip, Secondsync and Mesagraph in 2014 show that the Twitter wants to move beyond just advertising into the the world of social media data and analytics, especially for media, consumer companies and enterprises. The combination of analytics technology from Bluefin with the data APIs of Gnip make for a powerful combination and put pressure on companies like DataSift, FirstRain and other social media data and analytics companies.
On April 15th, Twitter announced that it was acquiring its longtime data partner Gnip for an undisclosed sum. Gnip is a leading provider of social media data, including Twitter data. Gnip has been a leader in the social media data market for a number of years, competing with the likes of DataSift, Topsy (acquired by Apple) and others. Companies like Twitter and Facebook have also offered this kind of information, but their social media data has traditionally been limited to one platform…
Prediction for 2014: Memory Optimized ("In-Memory") Database Technology Is Taking Over Enterprise Databases
Some are saying that the chip cache is the new RAM, and RAM is the new disk. In the DBMS world, this means that disk-optimized DBMSs (those that optimize their operations around the management of data on disk storage) are giving way to memory-optimized DBMSs (those that optimize operations around the management of data in memory, using disk for overflow and recovery purposes). A number of startups have unveiled exciting new technology along these lines. It's not just the startups that are having all the fun; leading DBMS vendors such as Oracle, IBM, SAP, and Teradata have also introduced DBMS technology that is either partially or entirely memory-optimized. This technology is sure to go mainstream in many enterprise data centers by the end of 2014.
Memory optimized database technology is that in which the internal operations of a database management system are optimized for the management and manipulation of data in memory, as opposed to optimization of data management on disk. This technology is commonly called "in-memory database (or IMDB)", but this term is somewhat misleading since it implies that the entire database must be in memory all the time, and this is not the case with most of the offerings in this space, nor should it be…
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Welcome to the Business Analytics blog where business and IT professionals engage in ongoing discussions on best practices, emerging market trends, and latest market developments in business analytics, including data warehousing, advanced analytics, query, reporting, and analytic applications.
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