8 Benefits to Using Document Understanding to Mine Unstructured Data

What if we told you that your business was sitting on a mountain of untapped business intelligence or that hidden away in archived emails, documents, and customer survey results are the very insights you need to drive growth and improve your bottom line? These types of text-based documents are a form of “unstructured data” and (alongside image libraries, data streams, and similar data deposits) account for nearly 80% of all the data that an enterprise company generates and stores.

How do you analyze all of this data to identify the specific insights that can drive change and improve performance in your organization? Through Document Understanding.

Understanding Document Understanding

Document Understanding is one of the three core AI capabilities fueling the unstructured data analysis industry (the other two being Computer Vision and IoT analysis). This system leverages the power of natural language processing and machine learning to analyze text-based documents (PDFS, notes, reports) to uncover actionable business insights.

The machine-learning capabilities of these systems allow your organization to “teach” the AI to read your specific documentation and discover insights that specific to your brand and audience.

8 Benefits of Analyzing Your Company’s Unstructured Data

The fact that the market size for natural language processing is estimated to reach over $16B by 2021 proves that organizations large and small are investing in tools and systems that analyze their unstructured data. This means that these companies are confident that the benefit of this work will outweigh the costs of these new systems.

While these benefits differ between industries, some of the key benefits to mining unstructured data includes:

1. Finding Opportunities to Improve Your Customer Experience

Retain more customers (and win over new fans) by using Document Understanding to analyze customer surveys and reviews to identify where your company can provide better customer service.

2. Discover New Opportunities in The Market

What is the “next big thing” in your industry? How will you ensure your company will stay relevant to consumers over the next 20 years? Turn your data lake into a blue ocean by mining your unstructured data for relevant insights and consumer trends.

3.  Know Your Audience Better With Sentiment Analysis

Use these systems to gain a deeper understanding of internal and consumer audience sentiment around your brand or a specific product.

4. Make Key Decisions Faster and More Accurately

Quit getting bogged down with analysis paralysis. Get the data you need to identify and take action on the “right” decision when it counts most.

5. Improve Team Productivity and Reduce/Remove Outdated Data Processing Techniques

Through automation, you can eliminate data processing bottlenecks and instead focus your employees on more high-value tasks.

6. Identify and Eliminate Unnecessary Cost Centers

Get a handle on your waste by understanding what areas of your business are costing you money (without providing a correlating ROI).

7.  Gain a Better Understanding of Your Customer Behavior and Buying Triggers

Improve the performance of your marketing campaigns and customer retention efforts by gaining more in-depth insight into what makes your customers your customers in the first place.

8.  Avoid Costly Regulatory or Compliance Issues

Uncover regulatory or compliance issues before they negatively impact your company.

Start with The End in Mind

Ready to get started analyzing your unstructured data, but not sure where to begin? We recommend starting with the end goal in mind. What is your highest unstructured data analysis priority? Are you sitting on a mountain of customer surveys? Are you curious about where your hidden costs centers are?

Understand which aspects of your unstructured data analysis will have an immediate impact on your business’s bottom line. Then work backward to develop the tools and systems you need to discover this intelligence.

If you are not sure where to begin, we can help. We’ve helped companies across a myriad of industries turn their unstructured data into business growth rocket fuel. Contact us today to learn how we can do the same for you.

If you’d like to learn more about how to unlock value from your unstructured data? Download our free eBook, “9 Steps to Unlocking Value from Your Unstructured Data and Content.”

Leveraging Machine Learning for Document Understanding

By: Troy Allen | VP Cloud Services

Businesses thrive on information, but due to the complexity and wide variety of data available within an organization, finding usable information can be challenging and time-consuming.  As organizations are inundated with documents, forms, data streams, and more, it’s becoming increasingly difficult to extract meaningful information efficiently, funnel that information into the systems that need it, and present it in a fashion that drives better business decisions.  Machine Learning (ML) and Artificial Intelligence (AI) tools are helping solve those challenges. ML and AI tools have rapidly become more sophisticated and capable of allowing organizations to gather critical information out of their content, rich media files, and data to facilitate better Document Understanding (interpreting unstructured documents into recognizable sets of information). Document Understanding is primarily focused on the information companies commonly mine: textual-based information, videos, and graphics. Amazon has recognized the importance of Document Understanding and developed services to help drive visibility and analysis that companies desperately need. Amazon’s Textract and Rekognition machine learning services are designed to gather meaning out of documents, rich media files, and data.

Getting More Out of Text

While Optical Character Recognition (OCR) has been around for many years, most organizations tend to overlook its strengths and ability to improve data processing.  Amazon Textract, while it does provide OCR functionality as a Cloud-based service, offers much more than one might expect because of its ability to bring Machine Learning-based models to business applications.  In order for data to be useful, it must first be collected; Textract goes beyond simple OCR by providing the ability to distinguish key-value pairs of information, table data extraction, and recognition of checkboxes and radio buttons.  Amazon Textract makes it easy to export the extracted data into a database or into off-the-shelf or custom applications. Traditional OCR solutions require additional tools to provide this level of data recognition and extraction.

More than OCR

Textract by Amazon Web Services goes beyond OCR by not only collecting the content but understanding where the content came from. Textract provides the ability to not only perform standard character recognition but is designed to understand formatting and how content is aligned within a page.  This is accomplished by recognizing and creating Bounding Boxes around key information and text areas to support the content, table extraction, and form extraction.

Amazon’s Textract retrieves multiple blocks of information from each page of the image it investigates:

– The lines and words of detected text
– The relationships between the lines and words of detected text
– The page that the detected text appears on
– The location of the lines and words of text on the document page

Table Data Exposed

Amazon’s Textract is well equipped to locate table data within documents. Textract recognizes the table construct and can establish key-value pairs with the cells by referencing the row and column information.

In addition to detecting text, Textract has the ability to recognize selection elements such as checkboxes and radio buttons.  A check box that has not been selected, such as  or Ο is represented as a status of NOT_SELECTED whereas checked boxes and circles are represented as SELECTED and can be tied to a key-value pair as well.  This can be extremely helpful in finding values in both tables and forms.

The Power of Key-Value Pairs

Businesses have been interacting with their clients and vendors for decades through forms. Textract provides the ability to read form data and clearly define key-value pairs of information from them.  Many organizations struggle with the fact that forms change over time, and it can be difficult to train legacy OCR tools to find data when those tools are specific to a particular form layout. Textract removes that limitation by reading the actual text rather than a location on a form to get its information and analyzes documents and forms for relationships between detected text.

Getting More from Images

Amazon Rekognition makes it easy to analyze image and video files using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. Amazon Rekognition provides the ability to identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. It provides those capabilities while also delivering highly accurate facial analysis and facial search capabilities that can be used to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.

Using AI to See More

With Amazon Rekognition Custom Labels, objects, and scenes in images can be identified for specific business requirements and actions. Models can be configured to classify specific machine parts, identify the use of Personal Protection Equipment (PPE) for employees from surveillance videos, capture model numbers in images, and detect persons of interest for image classification to name a few use cases. Amazon Rekognition Custom Labels allows organizations to quickly identify objects and images that have value to their specific business and processes.

Uncovering Hidden Data

As with Amazon Textract, Amazon Rekognition provides a way for companies to identify key information that can be stored, processed, and shared with other applications enabling greater Document Understanding across files and data.  Context of information is critical to assigning value and defining how it can be best utilized.

Amazon Rekognition helps companies realize value in their images and videos across many different use cases across the enterprise:

    • – Discover inappropriate content – filter images and videos for objects and scenes containing inappropriate content such as nudity, weapons, graphic violence, and even inappropriate text in the videos or images.
    • – Identify key objects – Amazon Rekognition can be utilized to filter Social Media video and image files to identify products, brands, people, and even landmarks.
    • – Help improve workplace safety – with the support of video, Amazon Rekognition can be utilized to inspect surveillance videos and identify issues such as people not wearing Personal Protective Equipment (PPE) and obstructive objects in the workplace.
    • – Support identity verification – facial recognition and person recognition can be accomplished through Amazon Rekognition by detecting humans, identifying facial features, and even comparing those to documented photographs of people for identifying people in images and video files.
    • – Capture text information – Amazon Rekognition also provides the ability to perform text capture and recognition in video and image files. This can help an organization gather data and information contextual to a video or image such as the model number of a part from a photograph of a manufacturer’s plate or even identify names of streets from street signs in a video to assist in determining the location of the event filmed.

You Are Not Alone

Business solutions can be complex, but making them work for your requirements doesn’t have to be.  Clearly defining your goals and objectives is half of the battle, the other half is knowing what tools will help you achieve those goals.  Are your off-the-shelf solutions and applications collecting all the information you have?  Do you need a business solution to manage all of your documents and data, but don’t know where to start?  Are you looking to move off an outdated legacy application that no longer supports your business direction?  You are not alone.

Thousands of companies are facing the same questions and are finding the best answers by engaging with experts from Amazon and experts from solution service providers. TekStream, along with Amazon, is excited to speak with you about your Document Understanding needs and how the right tools and solutions can have a positive impact on how you conduct business. TekStream is offering a free Digital Transformation assessment where we will work with you to identify your document processing needs and provide process and technology recommendations to help you transform your business with ease.  Reach out to us at info@TekStream.com for more details or call 1-844-TEK-STRM.

The Current State of Unstructured Data Analysis and What It Means for Your Business

The data analytics industry is continually evolving. What seemed like science fiction only years ago has become a business fact as new data analyzing tools and techniques come to market. And while larger organizations (with deeper pockets) have been the driving force of much of this change, advancements in artificial intelligence and machine learning have democratized big data analysis. Nowhere is this more apparent than the evolution of the modern, unstructured data analysis landscape.

Accounting for nearly 80% of all data generated and stored by an organization and growing at a rate of 55%-65% each year, unstructured data is one of the largest untapped and continuous sources of business intelligence. We’ve put this blog post together as an introduction to unstructured data and some of the tools and techniques that companies are using to analyze and mime their unstructured data for actionable insights to improve their organization and bottom line.

Understanding the 3 Different Types of Big Data

To understand what is meant by the term “unstructured data,”  you first need to know where it falls within the broadest categories of business data – structured data, semi-structured data, and unstructured data.

The below table compares the overarching differences between these data sets.

Structured Data Semi-Structured Data Unstructured Data
  • ●      Historically used for data analysis and mining.

 

  • ●      Data that is loosely organized by its source and delivery channel:
    • ○      Email
    • ○      Tweets
    • ○      Folders
  • ●      Data that is not organized in any way, which makes it difficult to process and analyze using traditional methods.
    • ○      Surveys
    • ○      External Industry Reports
    • ○      Data Analysis
  • ●      Designed for data capture, data input, data analysis, search, etc. within the document.
  • ●      Has some basic search/discovery
    • ○      Inbox Search
    • ○      Hashtags
    • ○      Folder Names
  • ●      Tends to be text-heavy but can include voice recordings, images, video, etc.
    • ○      Notes (handwritten or typed)
    • ○      Documents (POs, Resumes, Invoices)
    • ○      Rich Media (Geo-Spatial, Security, etc.)
    • ○      Analytics/Performance Data
    • ○      Internet of Things Usage Reports/Data Streams
    • ○      Customer Communications (Surveys, Live Chat, Automated Messaging)
  • ●      Pre-defined structured format with standardized columns and rows:
    • ○      Databases, Google Sheets, CSV, Excel, etc.
  • ●      Specific data within these channels is unstructured and text-heavy.

 

  • ●      Also known as qualitative data.
  • ●      Tends to be utilized within an organization according to data type.

As you can see, the definition of unstructured data is broad. There is no consistent medium or format, but most unstructured data is unstructured text: documents, social media posts, emails, surveys, etc.

So, how does a large organization mine swathes of unstructured data for nuggets of actionable gold?

The Current Environment and Capabilities for Mining Unstructured Data

As the importance of mining unstructured data grows, new discovery and intelligence tools are introduced to the market. Simultaneously, as analysis technology improves, more companies build systems and tools that have integrated data logging capabilities capturing and generating more unstructured data than in previous years.

This means that not only do companies of all sizes have access to more advanced data mining tools – they also have more extensive data sets to analyze.

In general, there are three core AI capabilities that are empowering unstructured data analysis:

Document Understanding: Fueled by natural language processing (NLP) and machine learning (ML), these systems analyze text-based documentation (PDFs, notes, reports) to uncover insights. The machine-learning capabilities allow you to “teach” the AI how to read your specific documentation and guide its insight discovery.

Computer Vision: This is used to analyze image and video content through digital imaging technologies, pattern recognition, and ML in order to process your visual data and uncover actionable intelligence.

Internet of Things: Here, data is generated from machines. AI relies on real-time analytics, ML, and smart systems to analyze the data for performance-improvement insight.

Document Understanding and Text-Based Data Analysis

We stated this earlier, but the vast majority of an organization’s unstructured data is text-based. More organizations are leveraging the power of Document Understanding systems to drive data mining and identify impactful findings.

Here are just a few examples of how companies are leveraging document understanding to fuel insight gathering:

  • – Sentiment Analysis: Automatically classify text by sentiment and pull together trend reports.
  • – Keyword Extraction: What keywords are recurring throughout a data set
  • – Regulatory and Compliance Support: Identify regulatory or compliance issues before they impact your business.

Getting Started with Unstructured Data Analysis

Ready to get started mining your unstructured data? TekStream has deep experience deploying both pre-built and custom unstructured data analysis solutions that empower teams with the insights they need to take action and improve their bottom line. Contact TekStream today to learn more about how we can assist your company with its unstructured data analysis goals.

Are you looking for more insights and best practices for unlocking value from your unstructured data? Download our free eBook, “9 Steps to Unlocking Value from Your Unstructured Data and Content.”

TekStream Launches AWS Content Process Automation Solution

TekStream, an Atlanta-based digital transformation technology firm, is excited to announce the launch of their new Content Process Automation (CPA) Solution. This new CPA solution enables users to quickly process and manage critical business documents, images, forms, video files, and unstructured data from a wide variety of sources through the power of AWS Integrated Services.

TekStream’s CPA solution automatically investigates content to find key insights and associations that might not be easily discovered by the naked eye. Users and administrators establish business rules defining what information is important, how it will be managed, and the final destination of documents, images, forms, video files, and unstructured data to ensure critical business facts and figures are available for business operations. Each department within an organization can benefit from TekStream’s CPA solution, but it may be of most use to departments including:

– Legal
– Human Resources
– Information Technology
– Marketing
– Sales

“TekStream has always focused on understanding our clients’ needs and providing solutions that ensure their success in reaching and exceeding expectations. Our new Content Process Automation offering is based on years of helping customers gain better insights from their managed content. With the power of AWS Artificial Intelligence and Machine Learning, we were able to create a solution that makes obtaining operational success that much easier to reach. We also ensured that our design is future-proofed by allowing more AWS services to be incorporated based on client needs or as new and more powerful services are offered by AWS,” said Troy Allen, Vice President of Cloud Services at TekStream.

Content Process Automation is a platform to build upon, as your business needs grow, TekStream’s CPA capabilities will grow to meet your requirements. As Amazon continues its investment in machine learning and artificial intelligence, TekStream’s CPA solution will incorporate those services to provide more options to make document understanding easier and more efficient.

TekStream

TekStream accelerates clients’ digital transformation by navigating complex technology environments with a combination of technical expertise and staffing solutions. We guide clients’ decisions, quickly implement the right technologies with the right people, and keep them running for sustainable growth. Our battle-tested processes and methodology help companies with legacy systems get to the cloud faster, so they can be agile, reduce costs, and improve operational efficiencies. And with 100s of deployments under our belt, we can guarantee on-time and on-budget project delivery. That’s why 97% of clients are repeat customers. For more information visit https://www.tekstream.com/.

Forwarder 6.x Compatibility with Splunk 8.0

By: Forrest Lybarger | Splunk Consultant

 

If you are looking into upgrading Splunk to 8.0, you have probably come across the compatibility matrix for forwarders:

Source: https://docs.splunk.com/Documentation/VersionCompatibility/current/Matrix/Compatibilitybetweenforwardersandindexers

 

This table means that Splunk does not support, nor has it tested, the use of 6.x forwarders with 8.0 indexers. It doesn’t mean that it is impossible for them to work together. In other words, you can use 6.x forwarders at your own risk. Any problems you have with these forwarders, however, will almost always be caused by the version difference and most likely fixed by upgrading.

With all the caveats out of the way, how do you get this working? Well, it depends on what exact version your forwarders have. Here are the affected versions:

  • 6.0.0 to 6.0.6
  • 6.1.0 to 6.1.4
  • 6.2.0 to 6.2.6
  • 6.3.0 to 6.3.1
  • 6.3.1511.1

The issue is that some older 6.x versions of Splunk use a different SSL protocol from 6.6.x and later versions, which makes them unable to connect via the management port (usually port 8089) and unable to communicate with the deployment server. To correct this, you need to force the newer Splunk components to use an SSL version that the older components can understand. In this case, your forwarders are the only components not upgrading to 8.0, so you only need to fix the deployment server. To avoid issues with these forwarder versions add an app with a server.conf containing this stanza to your deployment server:

[sslConfig]

sslVersions = *,-ssl2

sslVersionsForClient = *,-ssl2

cipherSuite = TLSv1+HIGH:TLSv1.2+HIGH:@STRENGTH

Allow any sslConfigs apps your environment already has to override this app by giving it a lower priority name or just add the lines from the stanza that aren’t present in your current app. You can delete this new ssl config after your forwarders are upgraded.

This fix should only be used if you must upgrade to 8.0 and can’t wait for your forwarders to upgrade. Keep in mind that this is not Splunk supported, so for now it could work (latest version as of writing this is 8.0.6), but in the future, Splunk could break this workaround. When you do implement this fix, make sure to prioritize upgrading your forwarders and understand that any problems involving data ingestion or forwarding are most likely caused by not upgrading your forwarders to at least 7.0 (latest version possible is recommended).

Want to learn more about forwarder 6.x compatibility with Splunk 8.0? Contact us today!

 

How Robotic Process Automation Fuels Document Understanding

By: Troy Allen | VP Cloud Services

RPA, or Robotic Process Automation, is becoming more prevalent in the world of business process automation. In its simplest form, RPA is the practice of utilizing bots or Artificial Intelligence to analyze information and make recommendations for actions based on that analysis.  RPA is not a static set of rules that a process follows. It is an evolving model that learns and adapts by examining recommendations and the actual actions taken and adjusts future actions based on what it has “learned.”  In short, RPA is business process automation driven by Artificial intelligence that learns as it goes to provide increasingly accurate actions and results.

As with business process automation, RPA can be utilized for many common tasks in an organization.  Insurance companies leverage RPA to automate the onboarding of new clients and validate insurance claims to reduce the amount of human-based processing while increasing accuracy.  Manufacturing companies utilize RPA to process Bill of Material documents and Purchase Order management.  Both examples focus on automatically processing documents and associated information that normally requires a high level of human interaction and decision making.

As an essential part of RPA, Document Understanding provides critical insights into the information being processed, helping to make the automation more accurate.

Document Understanding, a subset and critical function of RPA, interprets unstructured documents into a recognizable set of information that can be analyzed and acted upon with high levels of confidence.  Using specialized Artificial Intelligence tools, Document Understanding allows for the recognition of critical details and associations that would normally require human review to identify. For example, with forms processing and extracting key information from tables, Document Understanding enables RPA processes to perform highly accurate analysis and actions based on that information.

RPA and Document Understanding in Action

Onboarding new employees requires a large amount of information to be collected and processed.  Typical employers accept and track candidate applications, compensation details, candidate/employee profiles, onboarding documentation, performance management documentation, and various state and federal employee documents.  This can result in 15 to 20 documents being processed for each employee being hired.

Imagine an organization that hires thousands of employees for seasonal work, this can result in 2,000 or more documents that have to be reviewed, processed, and acted upon in a very quick timeframe.  Considering that a single document may take a human resource worker 2 minutes to review and make critical decisions about it, and up to 2 hours per document to complete its process, this can result in over 4,000 hours of processing.  Assuming the average resource cost for the participants involved in the processing of new employees is $25 an hour, the company could be looking at over $100,000 just to onboard these new employees.  This cost is most likely higher considering that not every candidate is a fit for the role or company and more candidates must be screened, interviewed, and processed to meet their hiring goals.

With RPA and Document Understanding, automated processes could be deployed to help minimize the amount of time each processor has to interact with the various documents and the actual process.  In many cases, documents can be automatically reviewed, analyzed, categorized, and routed for action based on a well-defined business process.  As an example, this can reduce the overall processing of those 2,000 employees from 4,000 hours to 2,000 hours, resulting in a $50,000 reduction in onboarding and hiring costs for seasonal employees.

What are the savings with RPA and Document Understanding?

As with any process, it takes time to establish, configure, test, and update to make the process as efficient and accurate as possible.  This is true with Robotic Process Automation and Document Understanding.  Many RPA tools provide a baseline of processes and intelligence based on business processes, but no two organizations operate the same way.

These baseline processes need to be modified to meet specific organizational operations.  In many cases, RPA and Document Understanding platforms provide a solid foundation to build upon which can save significant operational costs right out of the box.  RPA and Document Understanding are designed to learn as more information is processed which means that speed and efficiency grow exponentially.

Over time, organizations who utilize RPAs can see upwards of a 40% to 50% increase in efficiency and a reduction of 50% or more in processing costs.  The following chart outlines the potential return on investment (ROI) of an RPA solution with Document Understanding with 2 automated processes that traditionally take 4 full-time employees 35% of their time to perform with a salary of $55,000 annually per employee:

How to Learn More

Contact us to learn more about our RPA and Document Understanding solution – Content Process Automation (CPA) by TekStream. Through our experience and hundreds of implementations, we help companies streamline business processes and improve decision-making with a structured approach to unstructured content and data.

Using TekStream CPA, organizations can enable their users to quickly process and manage critical business documents, images, forms, video files, and unstructured data from a wide variety of sources. Fill out the form below to see how we can help you understand how Robotic Process Automation and Document Understanding can be leveraged within your organization. You’ll improve your processing efficiency, reduce overhead, and see a return on your RPA investment quickly so you can focus on driving your business to even greater heights of success.

TekStream Promoted to Premier Tier in Splunk Partner+ Program

TekStream, an Atlanta-based digital transformation technology firm, announced it has once again achieved Premier Partner status in the Splunk Partner+ Program.

In order to achieve Premier Partner status, partners must achieve $2 million in sales over the past 12 months and staff accreditations commensurate with the tier. With its Premier status, TekStream’s Splunk customers benefit from an enhanced level of engagement, commitment, and support.

By including TekStream in its Premier Partner Tier, Splunk has recognized TekStream for its outstanding achievement and commitment to Splunk market development, strategic prioritization, and customer success.

“I’m proud of our team and the hard work they’ve put in to achieve this accomplishment.  It’s especially impressive considering the circumstances we’ve all endured this year.  I’m excited about the momentum this creates heading into 2021 for our team, our customers, and Splunk” said Matthew Clemmons, Managing Director of the Splunk practice at TekStream.

About TekStream
TekStream accelerates clients’ digital transformation by navigating complex technology environments with a combination of technical expertise and staffing solutions. We guide clients’ decisions, quickly implement the right technologies with the right people, and keep them running for sustainable growth. Our battle-tested processes and methodology help companies with legacy systems get to the cloud faster, so they can be agile, reduce costs, and improve operational efficiencies. And with 100s of deployments under our belt, we can guarantee on-time and on-budget project delivery. That’s why 97% of clients are repeat customers. For more information visit https://www.tekstream.com/

OCI DR in the Cloud

Business Continuance via Disaster Recovery is an essential element of IT and takes on many forms. The high end consists of high availability solutions that provide real-time replication of systems. While these systems provide seamless continuity during outages they are large, complex, and expensive, justifiable to support only the most critical business applications. At the other end of the continuum, however, Disaster Recovery is little more than tape backup or backup to NAS which have complicated and lengthy restore procedures which take hours or days.
A major improvement can be made in disaster recovery with a solution that provides business continuity in a model that simply extends the existing IT architecture into the Cloud.

Rackware RMM Migration/DR platform is a non-intrusive Agentless Technology with pre- and post- Migration Configuration Capabilities that is easy to set up and configure for complicated enterprise environments/applications. Rackware RMM supports both Linux and Windows-based workloads for migration to the Oracle Cloud Infrastructure.

RackWare RMM platform provides a flexible and all-encompassing solution for Migration and disaster recovery. RackWare helps Enterprises and large Organizations take advantage of the agility promised by Oracle Cloud Infrastructure. Rackware’s platform eliminates the complexity of protecting, moving, and managing large-scale applications, including critical business applications and their workloads into the Oracle Cloud. It is now possible for enterprise customers to forgo the upfront purchase of duplicate recovery hardware, the cost of set up, configuring, and maintaining that hardware by leveraging Oracle cloud infrastructure.

Rackware RMM provides the following value proposition for enterprises in the Oracle Cloud:

  • Non-disruptive / Live Captures -No agents installed, safe and secure replication of your production environments
  • Network and Application Discovery – Automatically discover network configurations and applications allowing you to reconfigure them in the OCI environment during migration
  • Universal DR Protection – RackWare support spans all physical and virtual confluences, even for complex environments with Large SQL Clusters, and Network Attached Storage
  • Seamless Failback –  To physical and virtual environments, for simple disaster recovery drills
  • Cost Reduction – Orchestration engine for multiple polices of RPOs and RTOs based on tolerance to reduce costs with less expensive compute, network, and storage utilization.

Storage Methods

There are 2 storage methods available for Disaster Recovery.

Store and Forward

Store and Forward will create an image of your source workload in storage on the RMM’s database. When using this method, the RMM will need a datastore capable of containing the amount of used data from each source hosts minus typical compression savings.

Store and Forward is required if using the auto-provision feature whereby the RMM will only provision the compute resources during a DR event or test/drill event or to offer the multi-stage protection of having data protected by a stored image and then synced from stored image to target compute resources.

Passthrough

RMM does not store a copy of the used data from source hosts. The RMM acts as a passthrough proxy to sync the source workload data through itself and onto the target DR instances.

How it works

RMM provides a DR solution that builds on its image mobility and elasticity features to bring economic DR to enterprises. The building blocks of RackWare’s DR solution include onboarding, cloud bursting and the policy framework to automate necessary functions. Captured images from production (origin) instances are cloned and pushed out to a local or remote DR site. Changes in production images are periodically synchronized with the remote images, keeping the original host Image and the DR image in sync. In the event of an outage at the origin site, the up to date image at the DR site can assume operations through RackWare’s fail-over mechanism.

After the production instance is repaired and operational, it’s easy to restore the origin site to any up any changes made to the CloudImage in the cloud. When the origin site is restored to its operational state, the administrator can utilize the capture from cloud feature to refresh the original Image and synchronize any changes that occurred during the outage.

Overhead on the origin Host is extremely small involving only resources to take a delta snapshot. Thus the data overhead of the WAN link incurs only the delta of information, keeping bandwidth needs and sync time to a minimum. It’s important that Image updates include user data, Operating System updates, and application installations and configuration changes so that the recovery image behaves exactly like the production image should a failover occur. The cloud DR feature supports all of these. While OS updates are more infrequent it is still important to ensure that kernel patches are kept in sync with the DR Image. When updating the OS, an image refresh operation is done from the RMM first before the sync to the CloudImage. Should the production system be compromised or inoperable, the CloudImage is automatically launched and is running with the latest synchronized changes.

Oracle & Rackware partnership provides a seamless experience to Migrate to the Oracle Cloud Infrastructure and secure customer workloads with dynamic provisioning and disaster recovery.

About TekStream
TekStream accelerates clients’ digital transformation by navigating complex technology environments with a combination of technical expertise and staffing solutions. We guide clients’ decisions, quickly implement the right technologies with the right people, and keep them running for sustainable growth. Our battle-tested processes and methodology help companies with legacy systems get to the cloud faster, so they can be agile, reduce costs, and improve operational efficiencies. And with 100s of deployments under our belt, we can guarantee on-time and on-budget project delivery. That’s why 97% of clients are repeat customers. For more information visit https://www.tekstream.com/

TekStream Helps to Support the Launch of Professional Services in AWS Marketplace

TekStream, a digital transformation company and Amazon Web Services (AWS) Advanced Consulting Partner, announced today that it is participating in the launch of Professional Services in AWS Marketplace. AWS customers can now find and purchase professional services from TekStream in AWS Marketplace, a curated digital catalog of software, data, and services that makes it easy to find, test, buy, and deploy software and data products that run on AWS. As a participant in the launch, TekStream is one of the first AWS Consulting Partners to quote and contract services in AWS Marketplace to help customers implement, support, and manage their software on AWS. Click here for more information.

As organizations migrate to the cloud, they want to use their preferred software solutions on AWS. AWS customers often rely on professional services from TekStream to implement, migrate, support, and manage their software in the cloud. Until now, AWS customers had to find and contract professional services outside of AWS Marketplace and could not identify software and associated services in a single procurement experience. With professional services from TekStream available in AWS Marketplace, customers have a simplified way to purchase and be billed for both software and related services in a centralized place. Customers can further streamline their purchase of software with standard contract terms to simplify and accelerate procurement cycles.

“TekStream views AWS Marketplace as a strategic channel for our services to be discovered and procured,” said Judd Robins, Executive Vice President. “Complete solutions generally have a technology and a human component to make them work successfully. AWS Marketplace has always been a great catalog of technical solutions. With the addition of Professional Services in AWS Marketplace, customers now have a broader range of options to get those solutions launched and managed.”

• Database Migration QuickStart – Jumpstart your Database migration to AWS with a 1-week process to analyze and assess Oracle, Microsoft, and open-source database migrations to AWS purpose-built database solutions.
• Splunk Cloud QuickStart – Get your Top 3 IT Operations and/or Security use cases implemented leveraging Splunk with 2 weeks of services, training, and 3 months of go-live support provided by TekStream.
• Splunk CMMC QuickStart – a practical, proven, and effective solution to get you compliant in under 30 days.
• Oracle License Optimization Plan – 1 week to analyze and assess your Oracle licenses and contracts to reduce costs – paving your way to Database Freedom on AWS.
• CloudEndure Cloud Migration QuickStart – 1 week to Migrate Development, QA, or Testing On-Premise Workload to AWS
• CloudEndure Cloud Disaster Recover QuickStart – 1 week to implement and test disaster recovery for up to 3 on-premise workloads to AWS

TekStream accelerates clients’ digital transformation by navigating complex technology environments with a combination of technical expertise and staffing solutions. We guide clients’ decisions, quickly implement the right technologies with the right people, and keep them running for sustainable growth. Our battle-tested processes and methodology help companies with legacy systems get to the cloud faster, so they can be agile, reduce costs, and improve operational efficiencies. And with 100s of deployments under our belt, we can guarantee on-time and on-budget project delivery. That’s why 97% of clients are repeat customers.