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CIOs Continue to Overlook Simple IT Solutions to Automate Tasks

CIOs Continue to Overlook Simple IT Solutions to Automate Tasks

by Annette Dow

A recent research report by independent analysts Quocirca, points out that: “Thirty percent of an IT team’s time is spent on low-level tasks such as responding to minor user incidents, carrying out routine procedures or checking for errors.” The report concludes that: “One way to reduce the cost of performing such tasks is more automation.” (Tarzey Longbottom, 2012).

This is not news. I recall writing articles on this wastage of time, resources, skills and money back in 2009. Yet, here we are in 2013 and the wastage continues, despite an environment of ongoing budget cuts, layoffs and the need to do more with less.

Amazingly, CIOs and IT directors continue to overlook one of the most obvious ways to increase accuracy and efficiency while freeing up IT time to focus on more important tasks. The answer is staring us in the face: Automate those tasks that can be automated. And how? That’s easy: by using one of the most fundamental tools available to the IT professional – scripting.

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Backups: Insurance for SMBs in a Virtualized World

Backups: Insurance for SMBs in a Virtualized World

by Dan Nadir

The topic of health insurance can be a hot button issue for people. Some people simply want a high-deductible plan for emergencies, and others want coverage for more routine expenses. But when costly procedures start piling up, we can all agree that it’s best to have coverage to help us pay the bills.

Unlike individuals, businesses can’t afford to get philosophical when it comes to protecting themselves. Losing any important information, whether by theft or accident, can spell disaster. And it’s foolish to think it will never happen to small businesses. From outright attacks, to natural disaster, to employees losing laptops, the headlines are littered with examples of businesses suffering from information mishaps. And when you can’t replace the missing information, you just might be out of business.

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Tape's Modern Role as Shared Storage

Tape's Modern Role as Shared Storage

by Teig Lynster

The introduction of Linear Tape File System (LTFS) has changed the landscape for tape in the data storage industry. Tape as “NAS,” “tape appliance,” “Active Archive,” – these are all terms that will come to represent tape’s new role side-by-side with disk on the network. Tape is no longer just offline or near-line. It can be online all the time as shared storage. Indeed, tape has been repositioned as a hassle-free solution for companies looking at upgrading their data center environments.

This is a big deal, as the total cost of ownership (TCO) advantages of tape are even more important in an archive environment as data growth continues unabated. With this revitalization of tape, companies can optimize their archiving budgets and protect their bottom line. An independent study conducted by Brad Johns Consulting has found that LTFS is ultimately 80 percent less expensive to sustain and operate than disk-based archives. This is achievable as it is a lower-priced format and requires less energy to operate. While this is not groundbreaking news (the cost benefits of tape have always been apparent), the hassles and time commitment needed for operation have weighed in the minds of decision makers. After all, tape solutions have traditionally not been the easiest to handle, but the tides have changed.

Until recently, tape storage has been associated with offline capabilities. With the entire world moving online and going mobile, this comparatively primitive form of accessibility cannot be considered forward thinking or practical. It also would mean the inclusion of many extraneous intermediary steps between accessing information. With older archives, the data goes away and waits to be accessed, which usually involves a number of steps and the inclusion of an IT intermediary.

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Key Considerations for Managing Unstructured Data

Key Considerations for Managing Unstructured Data

by Shahbaz Ali

With data doubling roughly once every two years, combined with an increased focus on data protection and reliability the promises offered by new Big Data technologies, there has been a recent surge in interest regarding unstructured data management technologies and use cases.

With 80+ percent of all data estimated as being unstructured, there are significant opportunities for forward thinking leaders to gain advantage from improving what I refer to as the Three Pillars of Unstructured Data Management: Storing unstructured data; Controlling it; and Understanding it. A unified approach to unstructured data management can positively position almost any organization to gain benefits from reduced lifetime total cost of ownership and achieve a competitive advantage.

For purposes of this discussion, when we refer to unstructured data here, we are referring to all data that is not contained in a database format. This includes: emails and files from Microsoft applications; photos and video; imaging-related devices that span industries; mountains of sensor data from Mars to the deep sea – to name just a few of the many different types and originators of unstructured data. Each new day brings a new influx of data that is unstructured and can be measured in Petabytes.

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Apache Solr: Ready and Willing to Deal with the Onslaught of Scalable Data

Apache Solr: Ready and Willing to Deal with the Onslaught of Scalable Data

by Grant Ingersoll and David Arthur

“Big data” is an odd buzzword. It really is just data — the typical mix of structured, semi-structured and unstructured information that organizations have created, collected and analyzed every day for decades. There is just more of it. And even though these organizations are now dealing with billions of documents and terabytes of data, the real challenge isn’t necessarily around how to store this data. It’s really about how we can combine, analyze and search the different types of data in order to take better advantage of it.

What we’ve learned is that batch processing and simple reporting, even using new tools such as Hadoop to accelerate the processing of large data sets, cannot provide the full picture of what is happening inside this data. What’s missing? The very thing we take for granted every day on the web: Real-time, ad hoc search — that is, the ability to ask questions of the data using the tools and user interfaces we use in our everyday lives. In our experience, combining search with Hadoop and other big data tools enables big data processing to deliver a new level of understanding due to the ability to receive answers to questions in milliseconds instead of hours or days.

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