Advantages of Using Data Virtualization Software

Data virtualization is defined by Mousa, Shiratuddin, and Bakar (2015) as data management strategies that enable the retrieval and processing of data without requiring technical information such as its physical storage location or how it is formatted at its source. It offers a unified customer view of the data. It is essentially a technique by which data is stored in a way that specific web-based facilities can access it without being limited by things such as the type of file format or the person accessing it being required to supply the exact location of the file. Twitter and Facebook, as well as inventory management software, are common instances of data virtualization operations. These applications allow users to extract posted material without having to known the exact location of the servers.

Data virtualization is a dynamic integration approached that is used by organizations to gather more insight into their data hence, offer a faster and more calculated response to the fast-evolving business intelligence needs and analytics. Information technology pundits have also explained that firms can potentially save about 50-70 percent worth of resources as data replication would be limited. Also, the challenges of moving data that may never be used and the occurrence of data errors are eliminated. Data virtualization effectively prevents the “extract, transform, load” process that was typically involved with virtual data (Guo, Yuan, Sun & Yue, 2015). Consequently, it remains in the same place while real-time data access is available.

The data visualization landscape is a rapidly evolving field with players increasing each day. The hasty pace with which new firms are introduced into the industry each day indicates the immense potential of the practice. The superfluous of tech firms introduces the all-too-familiar challenge of competitiveness. Most entrants find it hard to survive, hence, bow out. However, there are firms that have consistently remained relevant despite the cut-throat nature of the business intelligence (Karpathiotakis et al., 2015). The top three players include Cisco, IBM and Denodo. Despite offering the same service, each firm presents its own unique set of merits and limitations.

Denodo

Denodo is one of the most dominant data visualization software and boasts of a significant market share in the sector. It is supported by Linux, iOS, and Windows (Vista and later versions) operating systems. In most situations, there are no additional supporting hardware other than the devices in which the software is installed on. As Guo, Yuan, Sun & Yue (2015) observe, computers with a random access memory of 2Gigabytes and a 64 bitrate or higher are the most ideal for running the software. Most services offered by Denodo are relatively cheaper than those offered by Cisco and IBM.

Pros

It is preferred by professionals, mostly because of its real-time data manipulation functionality.

One of Denodo’s key advantages is its competency in data mashup from different sources of data and returning different results in real-time. It is constantly updating the information it processes.

Denodo is one of the most efficiency data visualization software in the wrapping of databases and their subsequent presentation as web services.

It is best for instances where one does not want to have local storage as it has a vast virtual memory component.

Cons

A key limitation of Denodo is its inability to perform data aggregation and develop reports on local data.

Denodo is entirely purposed to meet business needs. As such, it cannot be used as a catching layer for general data analysis processes.

Oracle Data Virtualization (Oracle VM)

Business intelligence services giant, Oracle is one of the largest players in the data virtualization industry. Its product, OVM is available it two major firmware architectures; for x86 and for SPARC. OVM for x86 is a server virtualization platform primarily used for conventional on premise deployment and by private and public cloud (Blumenau, Sullivan & Murphy, 2015). The software is constructed and optimized for maximum performance, efficiency, and security. It supports most x86 hardware devices and traditional storage and computer-enabled devices that can run Oracle Solaris, Windows, and Linux.

Pros

The software supports application deployment from cloud to disc and as well as the reverse data cycle.

One of the key advantages of the platform is its live patching functionality. Traditionally achieved through KSplice, patching minimizes the disruption of services to the customer and enhances device and system security. Additionally, the software promotes hard partitioning, reducing application licensing costs.

Cons

Oracle VM is relatively more cost than other data virtualization software.

IBM PowerVM

Unlike the other two VM software brands discussed in this paper, IBM PowerVM introduces an entirely different perspective to the discussion as it exclusively operates on servers and associated hardware. It is primarily used to perform data consolidation of multiple workloads, hence, increase server utilization and cost reduction. The software offers scalable and secure server atmosphere for Linux, IBM i, and AIX applications with advanced features designed to yield high performance in its environment of operation (Blumenau, Sullivan & Murphy, 2015).

Pros

IBM PowerVM is often referred to as “limitless server virtualization” as a result of its relatively superior capabilities (Mousa, Shiratuddin & Bakar, 2015).

It is one of the most robust and efficient server virtualization software available as can consolidate data and tasks by up to three times, minimizing data replication by 100% to 333%.

Cons

It is only supported by AIX, Linux, and IBM i-enabled servers. It cannot be run on Windows or iOS-based devices.

Unlike OVM or Denodo, it cannot be used on portable or desktop computers.

It is expensive to set up as has elaborate supporting infrastructure.

Preferred Data Virtualization Software

My firm’s business intelligence and data management needs are centralized around the access, manipulation, and updating of data in real time. When one function of the organization inputs data into the system, it accessed by another department which then operates on to achieve a given end. The organization’s system continually analyzes and performs logical operations on the data as it streams in. Denodo software appears to be the most appropriate platform for the firm’s operations.

Denodo provides integrated access to the vastest range of organizational data, unstructured and cloud sources at a relatively low cost. It offers dynamic data management and service provision, presenting elevated business agility and return on investment (Karpathiotakis et al., 2015). The software’s primary source of efficiency is its creation of an integrated virtual layer of data that is easily accessible from all stations and that serves strategic industry-wide needs for single-view applications, cloud and web functions, and agile business intelligence interests.

The chief technology officer should explore Denodo as it offers a broad access to unstructured and unstructured data located in cloud, big data, and cloud sources. It offers users the luxury of viewing information in both real-time and batches hence, addressing the operational and analytical performance needs of our data-intensive organization. As a consequence, the company realizes faster marketing time and increased customer engagement. Lastly, Denodo software retains traditional extract, load, transform, aspects such as enterprise information integration, and data federation. As such, it provides a comprehensive and balanced insight of the data it analyzes.

Advantages of Using Data Virtualization Software

The organization is likely to experience reduced spending on information technology. Nearly 40% of the entire IT budget is spend on purchasing and maintaining hardware (Karpathiotakis et al., 2015). One of the most important yet expensive part of the process is the acquisition of multiple servers. Data virtualization requires way fewer servers as multiple tasks are consolidated. The reduced stress increased the lifespan of the existing hardware.

Data virtualization offers easier backup and recovery. One can never anticipate disasters with certainty, neither can they prevent them entirely from occurring. Theft, cyber-terror, power outages, and floods all represent threats to the company’s systems and may wipe of data critical to its operations, administration, or organizational memory. Virtualization enables data to be stored periodically in virtual locations hence, are recovered in an instant without the usual technical expertise or huge costs that would have been associated with the process.

The organization stands to realize much fewer data errors as the movement of data is limited. Information from an original source is available at different locations in real-time. This property also presents the advantage of reducing the workload and increasing the speed of access to data.

Disadvantages of Using Data Virtualization Software

The organization is likely to incur a huge capital cost during the purchase of the software and associated hardware (Blumenau, Sullivan & Murphy, 2015). The business might even require new employees to oversee the operation of the new system.

The response time of operational systems may be impacted especially if the system is not coordinated to manage unexpected user queries.

Rationale

I believe that virtualization software is appropriate for the company. This position is mainly informed by the fact that the software has the potential to open up many opportunities for the company. Traditional processes would be expedited as information keyed into the system from one location can be easily accessed in another in real-time without the need for specialized technical expertise. No periodic updates would be required for the information to be viewed or manipulated. Additionally, the traditional concerns of intrusion, data loss or destruction are effectively minimized. Virtualization offers for the storage of data in secondary virtual locations. As such, they cannot be easily accessed or destroyed should their source hardware been vandalized. Data virtualization would enable the company to utilize a significant portion of the IT budget as fewer resources are required for functions such as data storage and processing.

Advantages

Disadvantages

Computer Requirements

Initial Costs

Expected Savings

Reduced IT spending.

Huge capital cost to be incurred during the purchase of the software and associated hardware.

Denodo

Windows Vista and later versions

iOs 10.2

Linus OS

Windows; $159-$259

Linux $119- $499

40% of IT department budget is spent on acquiring and maintaining hardware will be saved

Data virtualization requires way fewer servers as multiple tasks are consolidated.

New employees might be required to oversee the operation of the new system.

Oracle VM

Windows x86

Oracle Solaris

Linux OS

(1) Oracle VM Premier Limited -> 1- or 2 socket server : $599 per server per year

(2) Oracle VM Premier -> more than 2 socket server (4, or 8 or) : $1199 per server per year (Blumenau, Sullivan & Murphy, 2015)

Man hours needed to perform multiple tasks will be saved as data virtualization consolidates tasks and performs them concurrently

Reduced stress on servers hence, increased the lifespan of the existing hardware.

The response time of operational systems may be impacted if the system is not harmonized to manage unexpected user queries.

IBM PowerVM

Linux, IBM i, and AIX applications.

Two 146 gigabyte 15,000 rpm SAS disk,

192 gigabyte memory,

24-core 3.5 gigahertz POWER8 processor

8286-42A5 rack-mounted server

$65,291.00

Easier backup and recovery.

Fewer data errors as the movement of data is limited.

Information from an original source is available at different locations in real-time.

References

Blumenau, S. M., Sullivan, J., & Murphy, C. (2015). U.S. Patent Application No. 14/789,345.

Guo, S. S., Yuan, Z. M., Sun, A. B., & Yue, Q. (2015). A new ETL approach based on data virtualization. Journal of Computer Science and Technology, 30(2), 311.

Karpathiotakis, M., Alagiannis, I., Heinis, T., Branco, M., & Ailamaki, A. (2015). Just-in-time data virtualization: Lightweight data management with ViDa. In Proceedings of the 7th Biennial Conference on Innovative Data Systems Research (CIDR) (No. EPFL-CONF-203677).

Mousa, A. H., Shiratuddin, N., & Bakar, M. S. A. (2015). Process Oriented Data Virtualization Design Model for Business Processes Evaluation (PODVDM) Research in Progress. Jurnal Teknologi, 72(4).