Cloud performance metrics News
May 05, 2017
This week, bloggers look into the Cisco-Viptela acquisition, barriers to hybrid cloud adoption and improving cloud analytics for midmarket groups.
April 10, 2017
As hyper-convergence matures, VMware bulks up vSAN 6.6 release with native encryption, analytics and improved availability, performance and management.
March 21, 2017
IBM enhances its cloud object storage based on Cleversafe technology with flexible pricing and a long-term, three-tiered cold vault object store for inactive data.
January 12, 2017
The International Institute for Analytics recommends embracing AI, clearly defining roles, and finding a balance between experimentation and deployment.
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For the uninitiated, analytics can be overwhelming. How you approach your first analytics project in the cloud can make it bloom or lead to doom. To hit the big time, start small. Continue Reading
Social media channels, web applications, sales and marketing systems and other sources are bursting with endless flows of consumer information pouring into corporate data reservoirs. The amount of data created annually, reports IDC, will reach a dizzying 44 trillion gigabytes in just a few years, and the storehouses to accommodate all that information are also growing exponentially. To mine gold from all those gigabytes and formulate intelligent business plans and sales strategies, organizations are turning to enterprise business analytics tools and techniques. Not surprisingly, two-thirds of companies surveyed by TechTarget plan to increase their spending on BI and big data analytics technologies over the next 12 months.
In the cover story of August's Business Information, editor David Essex examines three such organizations whose business intelligence strategies demonstrate the benefits of effective data analytics tied to key business applications, not to mention the hard lessons learned along the way. Oberweis Dairy is using enterprise business analytics software to improve the profitability of its home-delivery routes, outdoor clothing maker Arc'teryx Equipment brought two vastly different ERP systems together under one data warehouse roof for easier analysis, and the University of Michigan Health System's Fast Analytics team automated its once cumbersome, manually driven revenue-cycle reporting process.
In another feature, editor Bridget Botelho sheds light on the rapidly changing, complex world of enterprise application integration and the challenge to mix cloud apps with proprietary business apps to advance marketing intelligence and increase sales. Many companies lack a clear integration strategy and are falling behind in the race to integrate their data and applications. Yet many options are available to help them catch up, including cloud-based BI applications, third-party platforms and integration tools for non-techies.
Also in this issue, learn how a dynamic data analytics duo teamed with data visualization software to convince a traditional farm cooperative to abandon pen and paper and adopt a data-driven business culture.Continue Reading
Amazon CloudWatch enables administrators to track resources using metrics and log files. Admins should get to know the terminology as well as ins and outs of the auditing service. Continue Reading
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While many factory leaders are wary of the cloud, rejecting its use can hinder the ability to gain the benefits from smart manufacturing and IIoT. Continue Reading
The internet of things is in full swing -- but what will the next year bring? Industry experts look into their crystal balls and offer IoT predictions for the year ahead. Continue Reading
Smart cloud analytics platforms such as Salesforce Einstein play well as flashy demos, but they can have a substantive impact on day-to-day work in the enterprise. Continue Reading
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Expert Tom Nolle discusses how using a predictive cloud analytic project can help with future -- and current -- cloud computing performance and management issues. Continue Reading
What's in your toolbox? October's issue of Business Information turns the tables and puts that burning question to Capital One and several other business intelligence and data analytics software users. As the burgeoning worlds of structured and unstructured data collide, companies see urgency in predicting consumer behavior, technology trends and marketplace hiccups. Predictive analytics can foretell the future, but peering into a crystal ball chock full of statistics is tantamount to walking through a strange town with no street signs. Effective data visualization tools are the street signs in the form of easy-to-understand charts, graphs, illustrations and more. Visualized data helps business executives make sense of the analytics and arms them with the ammunition they need to see the big picture and formulate intelligent corporate, marketing and sales decisions. In a TechTarget survey on planned software investments, predictive analytics and data visualization tools top the list of BI and analytics technologies. But visualized data goes far beyond presentations for business executives.
In our cover story, reporter Ed Burns reveals that data scientists and analytics managers at companies like Capital One, Macys.com, BuildingIQ, ArcBest and Omega Point Research rely heavily on effective data visualization throughout the analytics process, from initial exploration to predictive modeling to reporting results. "Visualization is the bread and butter," says Boris Savkovic, lead data scientist at BuildingIQ. "It helps expose patterns over time as well as patterns between different variables."
The surge in predictive analytics and visualization tools can be largely attributed to the rise of big data. For IT teams charged with assembling big data architectures, editor Craig Stedman, in another feature, examines the abundance of technologies available and, paradoxically, the complications that creates. And therein lies the rub. "To pull it all together, I can say that 10 people didn't sleep for a year," relates Vinoth Chandar, Uber senior software engineer.
Also in this issue, learn how a security expert and cryptographer is using big data analytics and the cloud to make open source code safe for app developers and off-limits to hackers.Continue Reading
Cloud load balancing frees application server instances and provide enterprise IT with better overall performance, but current conditions make it hard in a hybrid IT environment. Continue Reading
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A successful cloud-based analytics implementation depends on following best practices to ensure that data from all sources is clean and current. Here are some tips. Continue Reading
A data analytics project often includes a high price tag and a long implementation cycle. Adopting Analytics as a Service can help with both. Continue Reading
There are six critical elements of cloud behavior that should be considered to meet performance levels in a cloud computing environment. Continue Reading