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Three Ways Enterprises Can Eliminate Useless Data

It’s an often-repeated adage in the business world that an organization’s information is its most valuable resource. But do we know what kinds of data corporations are actually storing? This may seem like a simple question to answer, but with the explosion of corporate data, most enterprises are unsure about what data they have, where they are stored, and even the value the data hold for the organization.

According to Veritas’ inaugural Data Genomics Index – a study that analyzed billions of files within actual companies’ storage environments – 41 percent of files within the average enterprise have not been modified in the last three years. And, even worse, 12 percent of files haven’t been opened in the last seven years. To put that into perspective, if 41 percent of data is stale, it means that 9.5 billion files in a 10PB environment have not been touched in more than three years.

These findings are so shocking that one would think that IT leaders were unaware of this potentially wasteful behavior. As it turns out, they had a hunch it was happening, but were blind to the details. An additional study from Veritas, the Databerg Report, revealed that global IT leaders believe only 15 percent of their data has any business value. And the remaining 85 percent is classified as redundant, obsolete, or trivial (ROT), or “dark data,” meaning the value is unknown – the data could be either critical to the business or completely worthless.

The lack of visibility into the composition of enterprise environments restricts IT leaders to a singular information management approach: assigning resources based purely on the volume of data stored rather than based on the actual value of the information to the business.

With this information management model, it’s easy to see how storage budgets can get out of hand quickly. For example, with more than 40 percent of the storage environment unmodified in three years, the average enterprise could spend as much as $20.5 million storing potentially unused data. In addition to the storage costs, the sheer clutter makes it harder for IT departments to identify valuable information throughout their environment potentially at risk.

To understand the immensity of the decision-making challenge that this presents, we can apply the perspective of a file-by-file oriented industry – legal document review. Contract-review attorneys churn through 50 documents an hour. At that pace, the average stale environment would take a little under 22,000 years to clean up. You could employ 22,000 contract attorneys for the next 365 days and pay them roughly $5.4 billion to clean up all the data. This is slightly more expensive than just moving the whole 10PB to Google Nearline for just $100,000 a month.

This hypothetical scenario may be exaggerated, but it hits at the heart of the information-growth conundrum. When facing an overwhelming number of information management decisions and drastically discounted storage costs, how can IT leaders break away from inefficient information management practices and catalyze change within their organization?

The Databerg report surfaced the beginnings of a path forward. It’s imperative for IT leaders to manage data based on its business value, not on the associated volume. This approach will free up budget through basic deletion of the ROT data and allow the enterprise to change its culture by taking the following steps:

    • Look to overrepresented file types. Traditional “office” formats like presentations, documents, text files, and spreadsheets account for 20 percent of the total stale population, so an archiving project focused just on these formats can cut costs by $2 million.

 

    • Understand the risk of orphaned data. Five percent of the average environment is orphaned data, or data without an active associated owner, typically the result of departed employees. When compared to the normal distribution of file types, this orphaned data is significantly more content rich – heavier in size and typically in the form of presentations, images, videos, and spreadsheets. This orphaned data is more likely to contain sensitive intellectual property, payment card industry, personally identifiable information, and customer information.

 

    • Create, implement, and enforce classification policies on users’ data. This can be difficult but it’s necessary to remain compliant and manage risk. Using classification to understand basic characteristics of the environment makes it easier to understand where critical information resides and who can access it. It’s also important to ensure that employees understand enterprise data policies through regular trainings.

 

By understanding the basic composition of the storage environment, organizations can take steps to focus their energy on smart classification, archiving, deletion, and data migration efforts. Regardless of where they start, organizations need this basic level of visibility to prioritize information governance efforts and start to save their environments from the crippling growth dynamic that enterprise data storage environments are currently experiencing.

Chris Talbott is Sr. Product Marketing Manager at Veritas. He works to bring Veritas File Analysis and Protection products to market and leads the Data Genomics Project. Before managing product marketing for the File Analysis portfolio, Talbott focused on the eDiscovery product line at Symantec, marketing, writing and speaking at industry events on the subjects of predictive coding and eDiscovery. Talbott joined Symantec from Clearwell Systems where he helped grow Clearwell into one of Sequoia Capital’s most profitable portfolio companies. Talbott graduated from the University of California, Berkeley with a degree focused on Globalization and Consumer Behavior.

Why Does Big Data Analysis Call for An Urgent Attention?

Data in the 21st century is no longer a file or two. If we consider the real-time big data constantly generated through various gadgets and users worldwide, the manual records seem quite illogical to handle the amount and operations. Do you think all this data is worth saving and analyzing? Let’s explore why it can be helpful for any business to record and monitor the incoming data constantly.

Recognizing the current trends and demands

Big data is generated by the customers and clients using e-commerce platforms or interactive websites to give feedback for the products and services provided by any business.

People’s choices for certain categories of products, their response to a new design or service launched, or their suggestions regarding the improvement of any existing can help the manufacturers and developers to think anew and develop their business strategies as required.

Better management of resources and funds

When the developers or the business managers have all the data and business records compiled together, they can easily decide and allocate financial budget and resources to different departments.

Big data includes the supply chain logistics, to and fro transactions of all the goods and supplies, and the rate of consumers’ demand for specific services. As the facts and figures are constantly updated, the owners can efficiently manage and distribute the resources.

Businesses can handle and monitor logistics easily

Modern business owners are entirely digitized so are their systems and procedures. Data storage and analysis no longer requires ledgers and records but depends on computerized databases.

No matter how much data is obtained every day, any business can automatically store all, constantly update the records, and even modify them as required. Without any tedious effort, the owners themselves can singularly handle the entire business logistics.

Organized business records are recorded on a single platform

The computerized storage of big data can be organized, unorganized, or semi-organized depending on the business sector and the amount of data recorded at a time. The databases usually store the entire data on a single platform, making it easy to handle the huge amount.

Compared to the manual records or the hard drives, used separately for different categories, databases can contain all on a single platform. Since the intelligent applications can automatically segregate and store according to the specific categories, they ease out the job eliminating the tedious efforts.

Easy retrieval of any demanded data

Data retrieval becomes a challenging task if the entire records aren’t organized in any fashion. Separate categories, quick keyword recognition apps, and smart output features of big data analysis are thus essential to categorize the entire data and arrange it for quick access. No matter how older or how small the query might be, efficient analysis and storage can help get instant results for any query.

Enhances security of the business data records

The entire business data and records stored on a single platform ensure safety from theft and leakage if the databases chosen are aptly reliable. The modern resources are generally tight with cyber security and phishing shields that help secure the records to a great extent.

Different Platforms and Software Available for Dynamic Big Data Analysis

If you are a trending business looking for the best resources to manage and analyze your large amount of incoming data, here are a few choices currently trending online. Apart from the generally available apps and online big data managers, these options are versatile and provide real-time data with efficient interpretation analysis.

Cloud platforms

Cloud databases are probably the most used for flexible data storage online. Any business or industry can opt for the public, private, or a shared cloud to store endless data in an organized fashion. The platforms can store, arrange and secure any amount of data and even provide servers and digital platforms to work on demand. Businesses can categorize and store their records to easily access them anytime.

Big data analytics software

Online tools and database software are widely available to store, manage and perform desirable computations on data. Hadoop, Cassandra, Spark, and STORM are a few trending examples now used by modern businesses and organizations.

The background software of all tools works on machine learning computations to interpret outputs to any queries shot to the database. Additionally, they provide an organized and categorized storage to access any data chunk anytime. A reliable database can promote secure storage along with amazing features to handle the bulk easily.

Digital workspace platforms

Microsoft 365 or Google workspace is a common term these days as many professions and businesses have stepped up online to work remotely. These workplace platforms are vast digital offices where the employers and the employees can collectively work on a single platform.

Roles, authorities, and access to different features are allocated according to the designations but the work being performed on a single floor collaborates the entire records. Effectively, they are a single database for the whole organization promoting easy access and management of all the organizational statistics.

Artificial Intelligence e-commerce platforms

AI platforms are the current tending digital spaces for all emerging businesses. The e-commerce website management software can collect data from different sources, arrange and store it as accessible records, provide a feasible workspace to modify and manage the logistics and interpret various outputs from the data available.

The artificial intelligence of these platforms can deduce the current business trends and analyze the demands and feedbacks using the customers’ activities on the websites. The owners can constantly compare their production rate, sales, and revenue obtained to upgrade their business strategies practically. Thus, along with splendid data storage, they also help with analyzing the trade.

Social media platforms

One of the most used advertising channels in digital marketing is social media. Apart from posting and advertising, these platforms actually help a lot to obtain and analyze dynamic data. The businesses using social media can interpret which of their services are more favored by their audience or the categories of the population most influenced by them.

The simple logistics like the number of likes and followers can indicate if the launching services are favorable or not. Social media, by large, also helps gain one-to-one feedback from the consumers as they can directly interact through comments and chats.