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Governance and Compliance are difficult to enforce in any environment, and even more difficult to enforce in a Data Lake which has many moving parts where users can interact with the data. Traditional systems and manual enforcement required all users to record the governance of what they did on the lake, ensuring they were recording and updating their most recent activity. This required that all users have the technical knowledge to update and maintain Governance tools and catalogues. This often resulted in users forgetting to update their actions or incorrectly coding the solution on the system. If all required actions are not 100% accurately recorded, there is a gap in your Governance and records, and it is not complete. This is the reason why more and more companies are removing the human element from the Governance and Compliance process and automating it instead. BDM Data Governance Procedures Automation ensures all key actions are recorded correctly and at the right time eliminating gaps in the recorded data and ensuring 100% compliance. Click here to learn more

Businesses today operate in an environment with an increased focus on data privacy where they need to remove the risk of exposure of sensitive information, while at the same time utilizing their data to get the maximum benefit from it for their business. New regulations such as GDPR require organizations to minimize access to raw data by their employees, while the value of sensitive data ensures that the risk of loss to third parties is greater than ever. The challenge for businesses is to ensure their data is anonymized in a secure and efficient manner as possible – and this is delivered with the BDM Data Masking and Tokenization solution. Click here to learn more

Poor-quality data undermines business digital initiatives and weakens competitive standing and leads to customer distrust. Given the growth in data that companies are seeing, which will continue to grow exponentially as 5G and IoT Data becomes more mainstream – validating the quality of data has to be seen as a process and not an end. As data changes rapidly the definition of what is accurate may change from day to day (or hour to hour), and you need a system that will capture these changes and identify the changes that are significant for your business. BDM has taken the best of these solutions, enabling you to record, measure and apply data validation checks, as it moves within your data lake. Whenever data is moved into a data lake, outside of a data lake, or within a data lake. This movement is carried out through a pipeline that is created in BDM and the data can be validated at all steps of the way. Click here to learn more

Businesses today are collecting, processing and storing data in unprecedented size and complexity. The regulatory environment has become more complex and onerous, with responsibility for the compliance firmly in the remit of the organization that owns the data. Captures all the data activities on your data lake and shares that activity with your existing catalogue and lineage solution with Bluemetrix Data Processing Platform. BDM helps you to track and prove the data lineage of all activities across your Data Lakes. Click here to learn more

Hybrid Data Processing is a consistent challenge for most organisations. As enterprises adopt cloud at scale across multiply environments, they soon realise they must now manage the native data processing services of each cloud vendor adding complexity and risk. BDM is a data processing layer that sits across all your environments giving you a single standard processing capability that you control. Click here to learn more

ING Bank Slaski is one of the largest banks in Poland with the majority owner being the Dutch ING Group. The bank has more than 300 bank branches, 4,400 ATM machines, and nearly five million retail customers. Always putting customers first, the bank offers user-friendly innovative financial products matching their needs. ING was awarded “Digital Bank of Distinction” by Global Finance in 2017 for its modern mobile banking application and is part of the UN Environmental Program, which requires organizations to take actions to reduce negative impacts on the environment. Click here to learn more

There is a growing need for data analytics in healthcare. The Covid-19 pandemic has highlighted the need for a more rapid response to healthcare crises and the ability to access vast amounts of data from disparate sources, for example for research and reporting purposes. At the same time, data security and patient confidentiality are paramount. Over the past six months, Bluemetrix has been working with leading healthcare providers in the UK to deliver a high-performance data lake that provides fast access to clean, accurate and governed data for analytical insights into Covid-19 patterns in West London. This system will, for the first time, provide the ability to manage access control to health data, allowing a full audit of every action taken. The insights garnered in the project show that data lakes have the potential to revolutionise the way healthcare data is collected and shared. The data lake solution is easily repeatable and adaptable in different scenarios and for different use cases in different healthcare niches globally. Better access controls with de-identified data for timely analytical insight Typically, data owners are reluctant to grant access to their data on the grounds that the requestor cannot guarantee appropriate processing of the data. BDM Health resolves this issue and for the first-time data requestors have the ability to address data owners’ concerns and convince them to allow access to their data. BDM Health comprehensively tracks and traces all data instances and data activities. Every access request and action taken on the data is also tracked and is auditable by both the data owner and data governance team. In fact, the data owner now has much to gain by granting access to a requestor using BDM Health; their data will be cleaned, tagged, and catagorised. Both metadata and business logic will be created and captured, making their data more valuable and secure than ever. Data owners can even create an approval workflow to have instant visibility into the use of their data. Using BDM Health, a modern informatics solution for healthcare providers, allows them to quickly access and consolidate data systems in a fully governed and automated way. The BDM Health solution for a unified healthcare data system Data lakes allow disparate systems - for example, medical laboratories, hospitals, GPs, primary care systems and electronic health records - to combine vast amounts of data in a central location securely and in a compliant manner. The resultant data lake provides a complete view of the data from patient, disease, care, and administration viewpoints. It also provides the necessary processing power and tools required to run AI and Machine Learning models, providing new insights into data from different sources in real-time. Benefits of the BDM Health solution Creating a unified data framework enables separate workflows for clinicians, researchers, administrators, and healthcare workers, building efficiencies across an organisation. The BDM Health solution provides a bird’s eye view of activities throughout an organisation’s IT systems and relates all activities to budget and real-time spend. Using high-performance big data analytics and input from multiple and varied resources, the BDM Health solution can drive targeted improvements in primary care and operational practices. Different levels of access to, and different views of, the data can be made available to selected personas - for example a GP may only view their own patients' data - ensuring patient confidentiality and compliance with healthcare regulations. Custom interfaces improve data sharing capabilities and empower remote users to collaborate more effectively across a unified network. In any organisation, data requestors and data owners need to be assured that data is secured, masked, and well-formed before transferring or receiving. BDM Health helps healthcare organisations define relevant access privileges, monitor data access and workflow processes, provide secure interfaces at endpoints, and ensure data is well formed at rest and in transit. Data lakes - an opportunity to address global healthcare challenges Data lakes offer national and international healthcare authorities the opportunity to pool their data resources and use AI-driven data analytics to better understand healthcare data issues. Using BDM Health automation, it is possible to quickly create a data pipeline that moves data from an EHR system to a data lake. This data pipeline is easily repeatable and completely scalable. The BDM Health platform’s data automation and data ingestion modules are powerful tools in all critical systems - safety, business, security, or mission. There is no other solution available worldwide on the market today that enables this kind of work to be carried out as quickly and comprehensively as the BDM Health platform does.

DataOps is the next generation of Data Management “Manually building data pipelines is the bottleneck to scheduling and delivering data to users. Combining DataOps & DevOps creates an intelligent digital business automation process that delivers higher quality data pipelines - Leonardo Dias, Head of Professional Services, Bluemetrix. In the digitised world of today, data is changing at the speed of light. DataOps is an innovative and collaborative platform that presents best practices to bridge the gap between those who collate data and those who analyse it. Under this model, both the development and operations teams can work together as a single unit during the entire life cycle of a product, while also keeping their tasks segregated. This ensures data integrity, streamlined processes, and allows each group to focus on their core competencies. The Significance of Intelligent DataOps Data is the main driving force behind a successful business. However, Data Operations come with many sets of challenges. In typical setups, 80% of data prep time is spent on creating a data pipeline along with manual activities circling data collection, securing the data, or providing data transformation and validation. This means only 20% of time is spent on running and managing the data pipeline. Secondly, the level of visibility for all teams involved in data science projects can be quite blurred, members often only see the bigger picture. Intelligent DataOps tackles these challenges head-on by delivering accurate processes, project details, and timely collaboration for all team members. The importance of well-executed intelligent DataOps strategy is underpinned by five core benefits as outlined below: Five Rewards of a Well-Executed and Intelligent DataOps According to data scientists, the amount of data doubles every 12 months, thus driving a high need for automating data operations. Data scientists spend a significant portion of their time preparing, cleaning, and labeling data to make it production ready. If Data Operations is well-planned and efficiently designed, organisations can reap meaningful benefits. Here are some key advantages: 1. Data-driven Businesses Companies that invest in Intelligent DataOps are data-driven and successful. With the advent of DataOps, the business world is seeing a rise in data-first organisations and according to the McKinsey Global Institute, these companies are 23 times more likely to gain customers, six times more likely to retain them and as an overall result, 19 times more likely to create a profit margin. 2. Agile Development Automated DataOps empowers data scientists to use agile DevOps methodologies that enables rapid iteration to improve models. The publication of newer models can be conducted independently in production without interfering with the development environment. Traditional data management runs on a Waterfall methodology where projects are executed with lengthy and intricate schedules with only one single deliverable as the result. 3. Enhanced Data Quality Due to the automation of analytics, code checks, and measured rollouts, Intelligent DataOps enhances data quality and elevates it to a new level. The minimisation of unplanned work, together with the automation of tasks, guarantees minimal human error transferred to servers thus avoiding downtime or any unplanned network outages. 4. Increased Efficiency Task segregation, coupled with coordination, is a key benefit of DataOps. It provides a bigger picture of dataflow which allows each team to focus on their areas of expertise without overstepping the boundary of other teams. However, if problems do arise, all teams can coordinate effectively and solve problems more efficiently. 5. Faster Delivery to Market In the digitised world of today, competition is steep and brand loyalty is diminishing fast. If a business cannot roll out features and functions quickly, they risk losing customers. Intelligent DataOps can significantly reduce the time to market business products from weeks to hours. Along with speeding up the delivery process, DataOps also provides the added benefit of agility that is a necessity in a rapidly changing market. Operationalising Intelligent DataOps for Analytics Intelligent DataOps provides a modern approach to creating and managing analytics. This approach reduces time consumption, minimizes unplanned work, improves data quality, and encourages a faster delivery to market. With the inefficiencies eliminated, different teams can work arm in arm to improve data quality by creating new models and analytics that stimulate business innovation and competition. Bluemetrix provides an Automated Intelligent DataOps platform creating the ideal foundation to support data management. Bluemetrix automates ingestion, schema evolution, governance, security masking, validation, and transformation. Bluemetrix, through automation reduces DataOps processing time by up to 70%, rapidly delivering production-ready data to analytics and data science teams.

The historical challenge of collecting quality data Enhanced data quality is an output when effective data governance is implemented across organisation. But, the process of operationalising data governance collection has challenges: Data sets that are often too small to be meaningful, reliable, or impactful. Data that does not accurately measure what it intends to measure or provide insights into end-user behavior. Human error when capturing data, including ambiguous, duplicate, and badly transformed data. Limited understanding of the business value of data governance. Lack of support from leadership and accountability for data ownership. Budget constraints and limited resources to data governance compliance tools. Lack of data documentation and understanding of who has access to it. Ninety percent of today’s data has been created in the past couple of years, according to an IBM study, hence the need to address the challenges of successful data governance simply, quickly, and cost-efficiently. On-demand webinar: Operationalizing Your Data Governance for Analytics Why is capturing data changes vital? Data in an organization changes on a daily basis. Some of these changes are critical to how an organization runs its business, and some have no impact. The dilemma facing executives is to identify the critical changes as they occur and ensure the relevant data owners are notified about these changes so they can act on them. Automation, correctly designed and implemented, allows these changes to be captured as they happen and brought to the attention of the people who need to know. Many organizations manage their data reactively, i.e. they only do something when they find an issue or error. According to Gartner's research, “the average financial impact of poor data quality on organizations is $9.7 million per year.” Furthermore, the cost of bad data can be an astonishing 15 percent to 25 percent of revenue for most companies. This is where Bluemetrix Technologies comes in, offering a proactive data governance solution for resolving bad data quality issues and enabling the automation of governance procedures in a controlled manner. Solution – Bluemetrix Data Manager Control 1. Monitor and report on data governance rules Bluemetrix assists organisations with enforcing data governance rules by monitoring and reporting on the real-world state of data at the company, for example, who has access to it, where it is located, and how sensitive it is, etc. The Bluemetrix Technologies game-changing plan of action: Data Access Auditing – Reporting on who has access to what data and how they use it. Data Quality Implementation and Reporting– Validating the consistency and integrity of data over time. Data Changes– Capturing change in the data as it happens and where relevant reporting these changes to the data owner/stewards. Anonymization of PII data –Mitigating security vulnerabilities, increasing security awareness, and creating customer trust and loyalty. 2. Monitor and report on the real-world application of data governance rules After successfully enforcing data governance rules, organisations may still lack visibility into the best way data is processed, updated, or changed. Bluemetrix Technologies can analyse data changes and show its effects, enabling the application of more relevant data governance rules. 3. Auto collect and populate data governance and catalogue tools Data is constantly changing. One of the biggest issues is capturing this change in an organisation’s metadata to ensure that the metadata always provides a true view of the underlying data. Bluemetrix allows the capture of this meta-data at the pipeline creation stage, and by automatically updating the data catalogue to represent these changes it helps data owners ensure their metadata is up to date and correctly represents the underlying data. Operationalise Your Data Governance Whatever an organization’s industry niche, they should not wait for false, irrelevant, obscure, or misleading data to create a hole in their corporate financial bucket. Operationalize data governance procedures can be done with self-service analytics that provide a fresh, simplified, and unified view of data across an entire organisation. We call it BDM Control – it will change the way you view automated data governance for quality data. 1. https://ibm.co/2Tu0CQG 2. https://gtnr.it/3jzKAPV

Business users want the ability to access the data they need for their pipelines when they need it. Traditionally users must wait for raw data to be ingested, processed and transformed to become production ready. This process can take weeks and months, at which point the data has lost much of its initial value. Typically, this process is manual and prone to human error which reduces quality and integrity of already derogated data. BDM enables you to reduce time to market and get your data when and how you request it. Click here to learn more

Automated data operations, orchestration & scheduling platform that manage engineering workflow and develop a data pipeline portability strategy for your team success. Click here to learn more

BDM together with Control-M from BMC, ensures the continuous integration of the data pipeline into a secure production environment, continually delivering the data from the pipeline to the end user. With Bluemetrix Data Manager, you can fully automate the process of big data ingestion, and provide a solid foundation for your Big Data projects, whether they are on-prem or on the cloud.