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Dark data sounds ominous and mysterious, but don’t worry. Although it sounds like something sinister, this type of data is no danger to your business.
It is actually the opposite – dark data can unlock a new world of hidden opportunities for your business.
Maybe the right information for your business is lurking in the dark, looking for the light of opportunity. This is not to say that sifting through this information is always easy. The process of finding hidden treasures in the dark can be very overwhelming and, without the right tools, sometimes very costly.
Today, we are casting light on the world of dark data, bringing in a kind of digital renaissance with the helping hand of cognitive automation. Unstructured data has amazing potential to streamline your processes, reduce cost, and make a bridge between sometimes completely unrelated information.
How can dark data help with better decision making, discovering patterns, and faster acclimation to changes? Are you ready to take that step in the dark?
What is dark data?
And what exactly makes data dark?
According to Gartner, dark data represents information assets that businesses collect and store during business processes but fail to meet their purpose and be used properly (monetizing, analytics, business processes, etc). To define it in simple words – it represents the information that isn’t well-defined, indexed, or easily searchable.
Dark data is often saved for compliance purposes, yet it hides the amazing potential
What percentage of data collection is considered dark?
Now let’s dive into some interesting dark data statistics to cast some light on the current state of things.
- Believe it or not, 80% of data is considered dark. It is estimated that this number will grow even more, up to 93% percent. This is because interconnected devices are constantly generating data.
- Why does dark data remain dark? Approximately 39% percent of companies are not equipped with adequate skills or resources or they are simply overwhelmed by the volume of constantly generated data.
- Because there is so much unstructured data being generated, 71% of executives are convinced that the value of the dark data will increase in the next ten years.
When we see things in this light we can conclude that forward-thinking business owners are well aware of hidden gems lurking in the dark. Most of them simply don’t have the resources to offset the risk or don’t have the necessary data-centric skillset to investigate unstructured data themselves.
Are dark data and unstructured data the same thing?
Unstructured data and dark data are often mentioned hand in hand and they mostly refer to the same thing. Unstructured data is data waiting to be refined and to be put to good use. Giving this kind of data structure and purpose can be a big challenge for engineers.
What is an example of unstructured?
Some dark data examples include log files, financial statements, customer call records, surveillance video footage, business emails, data about former employees, even notes, old documents, presentations and so much more.
How can the proper use of this data help your business?
If you analyze dark data you will get valuable insights about your customers’ likes and dislikes and will help you understand the customer’s journey much better.
In the post-Covid-19 era when we are still getting used to the new normal, eCommerce is on the rise. So in this era, personalization will play a major role. After all, no one likes to be treated as a statistic or referred to as “just a customer.”
Your customer is at the center of your business and the data surrounding them represents a unique puzzle and the faster you can solve it, the faster you can gain a competitive edge over your competition.
Acting in real-time is one of the crucial elements for harnessing dark data. If you store all the data it may lose its value as time passes.
How Cognitive Process Automation can cast light on dark data
There are so many buzzwords floating around in the ether nowadays such as machine learning, robotic process automation (RPA), artificial intelligence (AI), and cognitive automation. Although these sound similar, they are not. Each of them represents an important part of the transformation happening right before our eyes.
Cognitive robotic process automation is the extension of robotic process automation. Cognitive automation mimics human behavior and it is made for more complex operations such as analytics, recommending further actions, and judgment.
Contrary to RPA that works with structured and semi-structured data, cognitive automation works with unstructured data also.
Some areas of your business that can benefit from utilizing cognitive automation and putting dark data to use:
- Accounting: Invoices, orders, and purchase contracts are semi-structured data. Accounts payable can make the invoicing process more automated and cognitive automation can take a human role of opening emails, extracting the important data from invoices, emails, and documents. Dark data research is done in real-time, which prevents data from getting stale or forgotten.
- Customer journey made easier: Cognitive automation can make the customer journey easier in terms of security, analytics, and providing necessary assistance based on customer data.
- Retail: Cognitive automation can help with harmonizing data from different vendors in real-time, and it can help with proper product categorization. There are so many different formats when it comes to products — text, images, files, and more. Cognitive automation can harmonize all these elements and avoid costly errors.
- Document management and processing: Managing paperwork manually is behind us. Cognitive automation uses optical character recognition technology to scan different document types. This is important for industries like healthcare because many different documents and forms are used and each is important to ensure proper care for each patient.
- HR and employee onboarding process: Onboarding is a very time-consuming process. But thanks to cognitive automation, it can be efficient thanks to bots that, for example, can create logins for new employees.
By utilizing cognitive automation you improve the efficiency of your regular business activities by using large amounts of data that went under your radar for a long time.
Cognitive automation added to a human behavior component can lead to costs that are reduced by as much as 50%. (Source: Expert System)
Dark Data brought to light
Now when we put dark data in the spotlight, along with cognitive automation, are you getting some ideas on how to utilize this valuable, often misunderstood asset? Unstructured data and data analytics shouldn’t be complicated when we have such amazing technologies emerging.
Cognitive automation can improve your day-to-day activities. Bots that are learning from human behavior will bring structure to dark data and give it a purpose.
The B2B world is buzzing that Robotic Process Automation (RPA) is going to disrupt the way that organizations typically operate. But before we start painting the RPA town red, let’s stop and assess what the numbers and facts say first.
RPA is technology that is relatively new to help companies effectively transfer simplistic tasks from the human workforce to bots. These computer programs replicate the actions of the users, such as copying information, opening files, moving folders, etc. It then imitates those tasks with lower risks, higher efficiency, and decreased costs.
The technology has seen significant growth lately as well, in what it offers for streamlining enterprising operations and lowering costs. Additionally, what robotic process automation tools offer to the B2B market as a whole has spurned a sizable growth for the RPA market. Lead American market research company Forrester predicted that the RPA market will grow to $2.9b by 2020 which is enormous growth compared to 2016’s $250m market.
Let’s see some numbers first!
A comparable company Gartner has similarly reported, “Robotic process automation software revenue grew 63.1% in 2019 to $846 million, making it the fastest-growing segment of the global enterprise software market,” according to one of Gartner’s press releases. “Gartner expected RPA software revenue to reach $1.3b in 2019.” A year later, we witnessed significant growth. Worldwide, RPA software revenue reached $1.58b in 2020, which is 11.9% more. And what about 2021?
It is expected that global RPA revenue will reach $1.89b in the next year.
What do these numbers tell us? It paints a pretty clear picture that the potential and expectations of RPA are enormous. Additionally, the adoption within multiple industries has begun and the market valuation for those industries dealing in RPA is already increasing too.
Breaking it down: What is meant by “robotic process automation”?
RPA is a way to automate business processes. It’s an application of technology that is governed by business logic and structured inputs. A company can configure a “robot” (think: software, not transformer) to capture and interpret applications for manipulating data, triggering responses, processing transactions, and communicating with other digital systems. The use of RPA can range from something as simple as generating an automatic response to an email to deploying thousands of bots that are each programmed to automate individual jobs in an enterprise resource planning (ERP) system. RPA can automate any kind of process.
In the initial market adoption of robotic process automation, we are seeing mundane tasks being taken care of first as RPA can automate repetitive processes. Financial services firms were at the forefront of RPA adoption, figuring out ways to use software to facilitate business processes without increasing headcount or costs. Typically bots are easy to implement and low-cost without requiring deep systems integration or custom software. These characteristics are vital as organizations seek growth, without adding substantial expenses or friction among workers. When companies are trying to get some breathing room, they should look to RPA to automate the low-value tasks to serve their business better.
There are varying scales of RPA available. You could supercharge automation efforts by implanting cognitive technologies like machine learning (ML), natural language processing, and speech recognition, by then automating higher-order tasks that typically required the judgment and perception abilities of humans.
These kinds of RPA implementations (when it’s 15 to 20 automated steps) are part of a value chain known as intelligent automation (IA). Many experts opine that 100% of enterprises will have IA on their agenda for the next couple of years.
RPA in Practice: How has robotic process automation been implemented?
As constant pressure to increase productivity and reduce costs across most industries persists, many organizations are turning to RPA as a solution. RPA can be deployed on mundane repetitive tasks to free the human workforce to focus on other higher-level projects. Walmart, Deutsche Bank, AT&T, Vanguard, Ernst & Young, Walgreens, Anthem, and American Express Global Business Travel are among the many enterprises adopting RPA.
RPA helps companies from any industry complete a wide variety of tasks. As businesses are making their digital transformation, some implementations prove more universally successful than others. Here are a few of them:
- Help Desk – Being the first line to the user’s technical problems on your company’s website, RPA can help diminish the workload of the human IT team by taking care of repetitive issues with easy solutions. These first-level tech support issues are simple but time-consuming. It’s a perfect task for RPA to manage.
- Data Migration/Entry and Forms Processing – Employees are oftentimes obligated to pull relevant information from legacy systems to keep the data for newer systems. This tedious, manual process is common for human error and is easily translated for RPA systems. Tangible paper forms can be digitally transferred by an RPA solution that reads the forms and grabs the pertinent data.
- Pulling data from multiple websites to find the best deal – In RPA unstructured data finds purpose by scraping data off websites and setting up a comparison application. Whether you’re looking for flights, vehicles, or the best deal for trade show displays, RPA will be able to scan the internet much faster and efficiently than your front desk staff.
- Scheduling Systems – Online patient scheduling for healthcare appointments is a fantastic point for RPA technology enhancement. Gathering unique information per patient like insurance information, location preferences, appointment requests, and more can be a bot’s job within an RPA integration, freeing up staff for more qualitative tasks.
- Call Center Operations – Common customer questions and solutions can be provided to human agents via a dashboard that’s being supported with RPA technology. For instance, when an issue gets escalated to require human staff, RPA can help consolidate all of the information about this unique customer onto a single screen so agents are informed from multiple systems and can provide excellent service.
These examples just scratch the surface of how RPA can greatly impact productivity and efficiency in your company.
Limitations and Benefits: What Does the Future Hold?
Despite all that’s noted above, RPA technology comes with its own set of limitations. First and foremost, RPA won’t improve your processes. While it might be said that it’s not a flaw of the technology itself but more of the company’s systems in place – it must be said clearly: If you deploy RPA into a company with poorly-working processes, you’ll end up multiplying errors instead of fixing them.
Processing unstructured email content and capturing inputs from diverse formats are other issues facing RPA today. On top of that, RPA isn’t inherently a smart system. This means it cannot gain knowledge from previous experiences and therefore is unable to apply it to other dynamically evolving processes. Although there are additional technologies or modules offered by most RPA software packages that can be layered in with RPA to add artificial intelligence, “out of the box” RPA isn’t self-learning.
The benefits, however, far outweigh the limitations. The classic examples of processes ready to be automated are called “swivel chair” work. Meaning a repetitive, manual, soul-crushing, drudge work that requires zero creative input or problem-solving. RPA takes over this more “robotic” work…takes the robots out of the humans…and does it better and faster. That’s just the tip of the iceberg. When RPA is married to AI technology (Artificial Intelligence), it empowers imagination. Since these two are the match made in heaven and they can do magic for your business, consider buying AI add-ons with RPA from the beginning and you will be amazed by the synchronicity of these two.
How can business operations be seamlessly integrated into technology, work processes, and workforce? Here are a few of the top benefits of using RPA+AI
- Automate any business process from start to finish
- Connect front and back-office processes
- Organize and process complex data
- Eliminate errors and exceptions
- Strengthen operational security
- Ensure compliance
- Enhance customer experience
- Liberate employees
Ultimately, there is no magic bullet for implementing robotic process automation but it requires an intelligent automation ethos that must be part of the long-term journey for enterprises. Automation needs to get to an answer — all of the ifs, then, and whats — to complete business processes faster, with better quality, and at scale.
M-Files, at its core, offers all of the benefits of automated content and document management. Uninterrupted workflow, a single source of truth, and consistently accurate, up-to-date information available everywhere you need it at any time.
Access your information at any time, from any device – both online and offline.
M-Files Smart Metadata pushes the boundaries even further of what is possible with M-Files.
M-Files document management repositories are called Vaults. M-Files Smart Metadata is artificial intelligence working inside of your Vault. The application is an effective way to make your business processes operate faster because it is intuitive and straightforward to configure. The accuracy of the document classification feature itself is astonishing.
The more details you provide, the smarter it gets. Below we break down how M Files Smart Metadata can give a completely different dimension to your workflow and documents, their mechanisms, and how they work. Let us help you discover M-Files’ full potential!
What is M-Files Smart Metadata, and what does it do?
M-Files Smart Metadata is an application that utilizes machine learning to provide a more automated document categorization within the metadata fields stored with each asset.
All the documents are stored in the M-Files Document Vault. M Files Smart Metadata is a self-learning solution. Based on user actions, it listens and learns to provide suggestions in the M-Files Vault interface for both new and existing documents.
M-Files Smart Metadata automatically learns how to extract meaningful information pertaining to dates, names, and key organizations. What makes M Files Smart Metadata genuinely unique?
- M Files Smart Metadata automates the entire process. It works behind the scenes and improves its results with every use.
- M Files Smart Metadata gets metadata right the first time. It is incredibly intuitive and will extract pertinent data in a matter of seconds.
- Accurate and up-to-date information is available everywhere you access your vault.
- It works within the M-Files knowledge graph (more to follow) to bring together Artificial Intelligence and Machine Learning.
M Files Smart Metadata is included in all M-Files packages except Core.
What is the technology behind M-Files Smart Metadata?
M-Files Smart Metadata uses the M-Files knowledge graph.
The M-Files knowledge graph is a vault crawling application, a foundational component supporting the Smart Metadata service. M-Files knowledge graph adds intelligence and improves the features throughout the M-Files, keeping it in a constant state of evolution.
The knowledge graph is a service secured in the M-Files cloud, offloading heavy processing of new and existing content. It continuously works in the background to improve personalization, recommendations, and findability.
M-Files Smart Metadata can work with names, important dates, and organizations. The only condition is that information needs to appear within the document to extract it.
M-Files knowledge graph fundamentals.
- The M-Files knowledge graph resides in the M-Files Cloud.
- On-premise vaults can also utilize the benefits of the M-Files knowledge graph. It requires that the Vault information be shared, as well as documents sent to M-Files Cloud.
Which type of data is sent to the M-Files knowledge graph?
- Information from the latest version of any .doc, .docx, .pdf, or .txt file in the Vault is sent to M-Files knowledge graph. This includes the text contents of the file as well as its metadata property values.
- Data will remain in the M-Files knowledge graph as long as the document resides in the Vault. Once the document is deleted, data will also disappear.
What features does the M-Files knowledge graph include?
The M-Files knowledge graph crawling application indexes and provides metadata, enhanced findability, personalization, recommendations, and more.
M-Files Smart Metadata vs. M-Files Information Extractor?
Although these two sound pretty similar, specific nuances make M-Files Smart Metadata a more robust choice.
Let’s break down how the M-Files Information Extractor works. When you need the information to be extracted, for example, a date – the Information Extractor will extract every date present. M Files Smart Metadata, on the other hand, will withdraw the specific date requested.
Another difference between these two is the breadth of information it can sort. M-Files Information Extractor can extract other types of data (like personal information, phone numbers, geolocation, etc.) through regular expressions, and M Files Smart Metadata currently cannot do that.
When it comes to working environments, M-Files Smart Metadata only requires a connection to the M-Files cloud, whereas M-Files Information Extractor works on an M-Files server only.
If both are installed in one Vault, make sure to configure only one of them for the given metadata.
How much existing metadata is required for learning?
Approximately 100 documents will be needed to conduct successful training for artificial intelligence. However, it is also important to note that training is highly dependent on the consistency of your company’s documents. If you provide similar documents with all the required information and expected data, 20 of those documents are enough to establish a baseline.
In some instances, M Files Smart Metadata will not be able to learn, even though many document examples were provided. So for M-Files Smart Metadata to work seamlessly for your company, take note of the following:
- Keep consistency in documents and strive to template documents accordingly.
- Sometimes the documents are encrypted or scanned, so the M Files Smart Metadata fails to recognize the same metadata. Plan a unique ingestion workflow for these types of issues. The solution is to provide clear instructions to help it get the metadata right every time.
- Practice makes perfect and will help Smart Metadata learn.
What security and data protection safeguards does M-Files Smart Metadata have?
With security breaches affecting every vertical and industry, the protection of data is of utmost importance. Every request sent to M Files Smart Metadata is encrypted with an API key authentication. Every API key is uniquely generated for each Vault. Also, data is not shared between different Vaults. In terms of data protection, M-Files Smart Metadata ranks high.
M Files Smart Metadata is a breath of fresh air in the neverending sea of information. It will help you make your digital transformation faster. You will have accurate meta and classification information automatically. The best part is – it only gets better and more impressive as each day goes by.
M-Files Smart Metadata is growing and evolving alongside your business. Ask us how to make your business smarter.
I’m sure many of you saw the news yesterday about the massive data breach at Equifax. In this hyper-connected world we live in, it seems that hacks and cyber-attacks are becoming normal occurrences. According to the Identity Theft Resource Center (http://www.idtheftcenter.org/), there were 1,093 data breaches at U.S. companies and government agencies in 2016. This Equifax breach is worth your attention, however.
It’s estimated that 143 million customers had their sensitive data stolen from this consumer credit reporting company. Essentially, if you have a credit card or a mortgage, more than likely you were affected. Additionally, the type of data stolen makes this breach one of the most potentially damaging hacks we’ve experienced.
If you were affected, the hackers have your name, birth date, social security number, and address. In some cases the data contained driver’s license number, bank account numbers, credit card numbers, information about your mortgage and your payment history. Additionally, we found out that the breach occurred on July 29, so the data has been “in the wild” for 6 weeks. This is essentially everything needed to steal a person’s identity.
What can you do?
First, click this link to find out if your data was breached: https://www.equifaxsecurity2017.com/
Equifax is providing free identity theft protection and credit monitoring, which you can enroll in from this page.
Make sure your loved ones are enrolled as well.
Second, you could place a security freeze on your account at each of the three credit bureaus. It will make it difficult for people attempting to use your info to open new credit cards or other accounts.
The link to place a freeze or lift a freeze for each bureau is:
Third, since the breach took place a while ago, check your credit reports to make sure nothing has already happened.
Sr. Vice President
The Strickland Group