How Data is Stored and What We Do With It

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The amount of data in the world is increasing as our storage devices are becoming smaller and more powerful. With this abundance of data there is an increased focus on the ways we retrieve, manipulate, and use the data we’ve stored.

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Big Data

Today’s world is increasingly dependent on technology for a wide range of activities. From cultural growth and economies to political freedom, humankind now relies heavily on technology to store, manipulate and retrieve data. This dependence is exemplified by the huge amounts of data being processed on a daily basis.

Researchers estimate that humans are processing up to 295 exabytes of information (of which 2.5 exabytes of data are generated daily). The mind-boggling numbers associated denoted in exabytes come with 20 zeroes. In 2007 alone, computers processed 6.4 x 10^18 instructions per second. On the other hand, the storage devices used process big data are becoming more powerful in function and smaller in form.

Data and Large Companies

According to the State of the Cloud Survey conducted by RightScale in 2014, up to 87 percent of surveyed entities are using public cloud. Meanwhile, 74 percent of organizations have implemented a hybrid cloud strategy.

Technology giant, Google has the distinction of having the largest capacity to store data than any other entity. It is ahead of many other organizations, which are competitive in this regard. These include the National Security Agency (NSA), Facebook, Microsoft, Amazon, Chevron and more. The organizations spend billions building huge data centers Google has maintains data centers in different parts of the world, including Quilicura (Chile), Berkeley County (South Carolina, USA), Hamina (Finland), Dublin (Ireland) and many more.

Facebook reportedly collects up to 500 terabytes of user data daily. In addition, the social networking platform stores more than 100 petabytes of video and photos. The bulk of the data includes information related to user activity, such as status updates. With over a billion active users, Facebook handles up to 2.5 billion shared items, including wall posts, comments, status updates and more. Total likes in a single day reach up to 2.7 billion. Also, the users upload more than 300 million photos daily.

In turn, Facebook uses the big data to deliver relevant ads to users’ news feeds.

Document Retrieval Systems

Data retrieval has the capacity to present challenges when it comes to archival storage systems. The solutions need to provide reliability and sufficient capacity to store data for long periods. The data must be protected from unauthorized access and modifications. Any fragments must be identified and located in the archive quickly and easily.

Medical records are a good example of data that need to be stored for a couple of years. In some cases, organizations have to implement archives to meet compliance requirements. These regulatory obligations apply in a wide variety of sectors, including healthcare and finance. Meanwhile, one of the key characteristics of archival storage systems is immutability. This refers to the inability to delete or modify data before the end of the retention period. In such cases, files are usually assigned an identifier.

To expand storage capacity, organizations need to use data deduplication technology, which is also referred to as single-instance or intelligent compression storage. The technology eliminates redundant file from the archive. It is capable of achieving reductions ranging from 10 to 1 up to 50 to 1.

Powerful indexing and searching capabilities play an integral role in data retrieval. They make it easy to find specific files in a large archive. Searches can make use of metadata indexes to locate data. It is also possible to conduct deeper contextual searches of file content in documents and PDF files.

On another level, effective file retrieval is vital when it comes to compliance audits, litigation support services as well as e-discovery. Companies are usually given few weeks to provide data when a demand for discovery is issued. Failure to meet the deadline can have considerable financial repercussions for an organization.

The retrieval can only be conducted by authorized personnel with valid authentication credentials. The system also logs the activities within the archive for security reasons. This is aimed at preventing unauthorized deletion and file alterations. Data retention policies are required as part of legal and compliance obligations. However, retention periods for different file types vary.

Process of Data Manipulation

Data manipulation plays an important role in analysis. It involves the arrangement or sorting of data whether numerical, alphabetic, complexity or chronological. However, the process does not entail changing the data. Organizations can use data manipulation as a means to explore it or as a preparatory technique.

Unlike data transformation, no modifications take place, which is a fundamental difference with other techniques. Only the physical or logical relationship between data sets changes. Resorting the data provides a practical way to identify patterns that may otherwise be obscured.

The order of quantitative and numerical data can be changed through resorting. Doing so allows organizations to isolate individual values that are significant. On the other hand, rearranging involves the repositioning of a data element. This can be achieved physically or digitally. The rearrangements are usually exploratory and at times they are more directed. They make it possible to draw out common themes or grouping items into identical piles.

Some of the patterns used in analysis include trends, gaps, cycles, feedback systems, repetitions, clusters, pathways and more. Data manipulation allows design researchers and practitioners to immerse themselves in the data. They achieve the objective by compiling key observations and concepts. This technique is useful in both design and analysis. Manipulation is also used to carry out research on specific subjects. In a series of observations, researchers can sort data numerically or chronologically to discover the required insights.

Digital Transformation

Digital transformation has made it easier for both small and large organizations to take advantage of technology. The healthcare sector is using technology to improve patient outcomes. Medical facilities capture and analyze patient records to improve service delivery.

To become competitive, businesses need to process data much faster. They must achieve this goal regardless of the data volumes and complexity, which is constantly increasing. Many entities are faced with the challenge of managing data across various platforms, including cloud systems. In many cases, organizations have to replace their data management architecture to cope with the demands of big data.

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