Tag Archive for: compliance

Moving to the Azure cloud: unpacking dark data

Moving to the Azure cloud?

Today, more and more businesses are moving to the cloud – to automate and take advantage of AI and scalable storage, and to reduce costs over existing legacy infrastructure. In fact, in 2021, an estimated 19.2% of large organizations made the move to the cloud. And Microsoft Azure is close to leading that shift – with a 60% market adoption.

Often organizations focus on selected applications during a cloud transition. However, existing data might actually present the bigger complexity.  A majority of organizations use less than 50% of the data they own. At the same time, there is no oversight of data that is owned. This unused, unclassified, and unlabeled data is otherwise known as “dark data”, because it remains in the shade until abundant time is allocated to sort, label, and classify it.

Moving to the Azure Cloud is Like Moving House

We believe there is merit to comparing moving to the Azure cloud and moving house. You decide where to move, you choose your new infrastructure, and you get everything ready to move in. Then, you pack up your old belongings and move it with you. The problem is you likely already have plenty of boxes lying around. Think about your attic, your basement, and storage. Things from earlier relocations. You might have lost all knowledge of what’s in there. The same holds true when your organization’s applications and data must move house. But this time you also have to deal with ‘boxes’ of data left unlabeled by people leaving the organization, data left unused for a longer time, and data left behind from already obsolete applications. Moving this and other less well-known data may create bigger issues in the future.

  • Data is accumulating faster than it ever did before. You’ll have more of it tomorrow. Therefore now is the best time to go through data and categorize it
  • Proper governance of data is impossible without knowing its contents first. Older data collected from before GDPR regulations is still there. Compliance and Risk officers and CISOs dread this unknown data and fear it may fall out of compliance regulations.
  • It can be difficult to pass regulatory compliance audits with dark data ar If you can’t open a ‘box’ of data to show auditors what’s inside, you can’t prove you’re compliant.
  • You’re also not allowed to simply delete data. Industries and governments must comply with laws and regulations on archiving and maintaining open data.
  • When you know what data you have you can strategize and move towards controlled decisions on cold/warm/hot storage to optimize both costs and access. Moving data that is still dark may bring about irreversible data loss or at least expensive repairs in the future
  • Locating and accessing data requires the kind of information best-captured in classifications and labels, historical data analysis needs this metadata.
  • The parts of data that make up dark data leaves organizations vulnerable as it makes designing and taking security precautions extra hard.
  • Sometimes you can or must delete information. However, you can only do so if you know its contents beforehand and can determine regulatory compliance and have the foresight for future valuable analytics.

How can you optimize accessing this data? When one of our clients, the Drents Overijsselse Delta Waterschappen, looked at archiving and storing its past project documentation in the cloud, it found the necessary manual labeling a daunting task. The massive time-investment needed is very similar for other organizations making a cloud transition. Manually reviewing data is simply too labor-intensive for most organizations to undertake within a feasible timeframe.

Unpacking Data with Synerscope’s Ixivault

With Synerscope, you can achieve the data clarity you need. As a weakly supervised AI system, our solutions are built to perform where standard AI approaches would fail. Synerscope’s Ixivault implements onto your Azure Tenant – with no backend of its own. This means that all data stays inside your tenant, which is a big plus for all matters and concerns regarding security, governance, and compliance. Our friction-less implementation then allows you to open up, categorize, and label dark data using a combination of machine learning with manual review to speed up the full process by an average of 70%.

Ixivault analyzes your full data pool of structured and unstructured data, creating categories based on data similarities, pulling keywords and distinctive terms, and generating images of those data stacks – which your domain expert can then sit down to quickly label. Most importantly, Ixivault has built-in learning capabilities, meaning that it gets better at categorizing and labeling your specific data as you use it.

All this makes Ixivault the perfect tool to help you move – by unpacking boxes of data as you move them to the cloud. You can then choose appropriate storage, governance and access controls, even if you need or don’t need to keep the data. For the first time you can have a near edge-to-edge overview of all your data with zoom in options to very granular levels so you can make the best choice what to do next with this newly discovered data. Having new information about your data can make you money and save you money all at the same time.

If you need help with unboxing your dark data as you move, contact us for more information about how Synerscope can help. You may also purchase the Ixivault app directly at Microsoft’s Azure Marketplace.

Ixivault Helps Labeling and Categorizing Dark Data in the Azure Cloud

Ixivault, a managed app on Microsoft Azure

Your organization’s dark data presents challenges when you move to the cloud. Yet, leaving it in a current location is also not the solution.

Dark data includes digital data which is stored but never mobilized for analysis or to deliver information. If you have dark data, your organization is already missing opportunities to derive value from it. However, if you don’t take dark data with you to the cloud, it drifts even further from your other data assets. Meanwhile, the flexible computation and memory infrastructure of the cloud offers a very cost-effective solution to mobilizing that data. Most importantly, it does so at any scale your organization needs.

However, there are still challenges here. For example, overcoming the risks of governance and compliance, increased storage costs, and storage tiering choices. Do you choose to store data in close proximity to synchronize with other data – but at a higher storage cost?

Migrating Dark Data to the Azure Cloud

For most organizations, failure to create and execute a dark data plan as part of the cloud transition is undesirable at best and breaching data compliance at worst. Synerscope delivers the tools to analyze and “unlock” that data during the transition, making efficient use of cloud computing, while keeping data in your full control. This means no additional risks arise for compliance, security, etc.

Synerscope also helps you mobilize dark data, using a combination of machine learning, AI, and human expertise. Unlocking dark data is essential for most organizations. That remains true whether you’re shifting from legacy systems to Azure, are reducing your governance footprint, or are pressed into unlocking data for compliance or a regulatory audit. Synerscope’s Ixivault comes into play at any point where you need detailed and broad overviews of complex data. This is achieved through sorting, categorizing, and revealing patterns and giving domain experts the tools to label categories at speed, with high accuracy.

Your Data, Your Azure Tenant

Ixivault is a managed app on Microsoft Azure. When you deploy the tool, it installs on top of your Azure Blob or ADLS where the data stays in your control. We power Ixivault on Azure computing, meaning that it dynamically scales up computing power to meet the size and complexity of the data you direct to it for scanning and computation. At no point does the data leave your Azure tenant or any assigned secured storage used before separating sensitive data out. SynerScope’s design suits the most stringent demands for compliance and governance. Our Ixivault feels and operates like a SaaS but does so in your tenant, without any proprietary back-end for storing your data assets. Therefore, Synerscope allows you to categorize, sort, and label your dark data without introducing additional regulatory complexities. Your data stays in your cloud, the process is fully transparent, and you control and monitor your tenant for all matters related to data sovereignty.

That applies whether you’re importing data to Azure for the first time to inspect before deciding where to store it or already have data in a Blob or ADLS and must inspect it or want to open data on legacy infrastructure.

Sorting and Categorizing Dark Data

Ixivault leverages AI and machine learning for sorting and text extraction. Here, visual displays offer domain experts rich and discerning context from which to choose the most suitable labels of descriptive metadata. Our technology is a weak supervised system, first unsupervised computing handles the data in bulk, followed by a human operator to validate labels and bulk sorted data categories. The system works on raw data inputs directly, without training. Using raw data sets with human validation to add labels means we can make the system smarter over time. Future raw data sets are automatically checked for similarities with previously processed data sets. So, high value can be achieved from day one, but the system learns over time. .

Ixivault abstracts data to hypervectors – comparing the similarity between data algorithmically. Using algorithms, the AI can accurately sort data into “Stacks” of similar files. Format, lay-out and content of documents are all used by the algorithms to separate common business documents e.g., contracts, letters, offers, invoices, emails, brochures, claims, and different tables. And our algorithms separate sub-groups according to actual content within each of these. Our language extraction presents distinctive groups of words from each “Stack”, allowing humans to select the most appropriate labels. The same extracted words can also be matched to business glossaries and data catalogs already available to your organization. Hypervectors allow our algorithms to detect similarities across documents ‘holistically’, at a scale beyond unaided human capacity. The resulting merge of rich ontologies and semantic knowledge are re-usable throughout the organization and the many applications it runs.

Machine Learning with Human Context

Ixivault creates outputs that allow your data experts to step in at maximum velocity and scale. The application displays a dashboard showing the stack of data, visual imaging of what’s in this stack, and keywords or tags pulled from that data and metadata. Where descriptive metadata is lacking or absent, our system presents new candidates for labels. The system supports users in running fast and powerful data discovery cycles, which link search, sorting, natural language programming, and labeling. The output is knowledge about your organization’s dark data which can be used and reused by other users and software systems.

This approach allows data experts to look at files and keywords and very quickly add tags. More importantly, it creates room for human expertise, to recognize when data is outside of the norm – e.g., files are related to a special circumstance, which machines simply cannot reliably do. The result is a powerful, fast and flexible system, usable with a variety of data.

Once you select the machine proposed labels, you only have to individually inspect a small number of the actual files to confirm the labeling for an entire group of sorted files.

Unlocking Dark Data as You Move to the Cloud

Moving to Azure forces most organizations to do something with, or certainly think about, their dark data. You can’t move untold amounts of data to the cloud without knowing what’s in it. You would not be able to extract enough additional value from such a blind move. Directing data to the right storage solutions for easy governance, compliance, and management demands knowledge of its content. E.g., so you can prioritize data for further processing and computation, or save on storage for less value-added content. Data intelligence can mostly be paid for by decreasing ‘dark storage’. Meanwhile, your organization can improve its governance footprint and ensure compliance.

Synerscope can deliver the potential value in dark data by increasing knowledge, helping with retention, access management, discovery, data cleansing efforts, data privacy protection measures, and compliance. Most importantly, dark data mining gives organizations the information needed to make business as well as IT and compliance decisions with that data – because Data intersects between the three.

To learn more about Synerscope’s software and our approach, contact us to schedule a demo and see the software in action.

Delving into Dark Data on Azure – Data Governance in the Cloud

For most organizations, dark data is a vague concept, the knowledge that, somewhere, you have vast amounts of stored data – and you have no real idea what it is. Gartner coined the term to refer to data which organizations collect but fail to use or monetize, and eventually lose track of.

That data, which is stored in network file shares, collaboration tools (e.g., SharePoint), online storage services like Drive and Dropbox, old PCs, and backups, is dark because most people in the organization have no idea what’s in it. In fact, often that data is stored in legacy systems or placed on drives by people who have since left the organization. But, as organizations move to the cloud and must choose whether to leave data where it is or move it to an Azure Blob, it becomes more of an issue – not just for the potential of business value but for regulatory compliance.

Dark Data can include Private Data

Dark data offers no promises in terms of delivering business value. Yet, organizations cannot ignore it. Often, dark data contains everything from personally identifiable information to HR data, legal contracts, security, and access information, and other confidential or proprietary information. This presents real liabilities in information governance, especially in industries such as finance and public sector. And, for global companies, it becomes increasingly crucial that data analytics and governance be addressed simultaneously to meet data privacy laws across the EU and USA.

Knowing your enterprise data and being able to search for it would be the ideal. However, the absence of labels, categories and meta data in general makes it hard to choose what to send to AI for analysis and discovery, who receives access to what data, and what data to keep (and where to keep it). Most businesses have dark data specifically because it takes too much manual effort to sort and label. But dark data presents unknown potential and risks – without understanding its contents, no organization can optimize decisions around what to do best.

A Significant Governance Footprint

Both structured and unstructured data can be part of dark data. More unstructured than structured data resides in the dark.

Why? Unstructured data makes computerized processing more difficult, much of this data requires significant manual processing.  Azure cloud compute and storage use elasticity and scale to offer options to optimize resources efficiently and cost-efficiently process all data. This option is obviously not readily available in on-premise data centers. With SynerScope positioned on top of the customer’s Azure object store (Blob or ADLS), enterprises can quickly and economically see what content they have. More importantly they can use this information to take action.

For example, the underlying contracts and correspondences for 10-year-old invoices cannot be handled without proper governance. In the Azure cloud, you can generate that data. Yet, if there are multiple back-ends from different SaaS suppliers, moving dark data to the cloud is impaired from a governance and risk perspective. That’s why SynerScope’s SaaS-like application uses the storage on the customer’s Azure tenant. Therefore, all data protection and security is regulated by the single contract between the customer and Microsoft Azure. This simplicity allows the enterprise to confidently move data to the cloud, knowing that responsibilities and liabilities are clearly defined.

Categorizing Dark Data in the Azure Cloud

At Synerscope we deliver the tools to unlock dark data using machine learning for sorting by content, whilst your domain experts add context. Our AI sorts data visually, “stacking” content based on visual similarity – and highlighting keywords and descriptors pulled from the stack. Your domain expert can use that to add context to the stack – quickly identifying whether something is an invoice, a mortgage receipt, a single customer’s banking data, etc.

The software installs into your Azure tenant, leaving data in a system structure, only governed by your Azure contract. SynerScope runs similarly to an Azure module; we bring data to cache memory, it is computed, and newly generated metadata augments the original data. These data artefacts are moved into the storage, which you, as a client, set up and manage. We provide the support for you to:

  • Find relevant structured and unstructured data, open it for control, data governance, and maintainability for GDPR compliance
  • Find and structure data for governance to meet compliance requirements in finance, public sector, etc.
  • Improve triage for files to be inspected in KYC, CDD, PDD, and AML investigations

Most importantly, this applies both for stored dark data – and for the massive quantities of data churned out by CMS, self-service, surveys, and specifics like KYC programs and security. Synerscope delivers tooling to make the move to the cloud possible with dark data analysis – so that the organization implements proper governance on all data as it moves to the cloud – while creating structure and insight into new data.

Granular Insight into Big Data

Synerscope gives massive insight into not just dark data, but any data. By mapping data visually and relying on data experts to create connections, we speed up data analysis across nearly any type of data.

In a specific example, KYC is incredibly important for banks and other financial organizations. Automatic alert systems can have as much as a 5%+ false positive rate – each alert requires manual review. If each manual file review takes 4+ hours, a 5% false positive rate is a massive burden on the company. But Synerscope’s machine learning using AI to categorize and sort data, speeds up this manual review by as much as 20x.

As data continues to accumulate in the cloud, Synerscope’s role in making day-to-day compliance and governance decisions will grow. That applies for retrieving data, deciding where to store it, and whether to keep that data in the first place.

If you would like to see how it works, contact us for a demo or pilot

Tag Archive for: compliance

Webinar (in Dutch) – How insight into “dark data” contributes to a data-driven Waterschap (Water Board)

SynerScope is hosting the following webinar (in Dutch):


This webinar will provide you with new insights about the strategic use of data to optimize processes and offer more transparency in accordance with government guidelines.

For further information and registration, click here.

 

Speakers


Jeroen Waanders
Adviseur innovatie – Waterschap Drents-Overijsselse Delta

Webinar (in Dutch) – Compliance 2022, how to organize ‘next-level’ insight into data?

SynerScope is hosting the following webinar (in Dutch):


This webinar will provide you with new understanding of ‘next-level’ data insights and will prepare you for increasingly stringent compliance requirements.

For further information and registration, click here.

 

Speaker