Use Cases & Case Studies

MANTA Cases #4: Patient Zero (How it all began)

Have you ever wondered how it all started back in the day? Well, as another part of our MANTA Cases series, we’ll introduce to you the very first way MANTA was ever used, “Patient Zero”.

Have you ever wondered how it all started back in the day? Well, as another part of our MANTA Cases series, we’ll introduce to you the very first way MANTA was ever used, “Patient Zero”.

Patient Zero of MANTA was a member of the Société Générale Group, the Czech bank Komercni Banka. Back then, MANTA was no more than an internal tool of a Czech consultancy company, Profinit, which was hired to solve a data quality issue within Komercni Banka.

The problem was that some parts of Komercni Banka’s data warehouse had different coding because of special Czech diacritics that were more space-consuming than regular letters and symbols. This was creating a lot of mess throughout the piles of custom code. The customer was using a Teradata database, whose price varies according to the amount of data stored. As Komercni Banka had to store a phenomenal amount of customer data, they were trying to store it as compactly as possible to save money on database space.

In a Teradata database, you can store data in Unicode or in ASCII. In Unicode, you can store Czech letters like “š” or “ů” or any other language-specific symbols, as it has a larger format. ASCII is able to store only classic letters and numbers, but therefore takes up less space on the database. As not all Czech words and names have diacritics, this was an opportunity to store some data in a more compact format. (This use case could work with any language that has language-specific symbols, not only Czech.)

Komercni Banka first looked into the source systems to identify all source columns in the database that might have contained Unicode and those that contained only ASCII, and with the help of MANTA, they identified where the Unicode data was propagated and where it was clear that there was only ASCII data. After that, the company used MANTA Checker, a tool that MANTA originally developed to quickly fix errors in code, to perform an automatic add conversion function to the data that could be converted from Unicode to ASCII.

The bank has estimated that thanks to the use of both MANTA and MANTA Checker, they have saved quite a lot of money on storage fees, freed up several FTEs in the organization, and have been able to both monitor their environment and develop new code more efficiently than ever before.

Want more information about MANTA or MANTA Checker? Don’t hesitate to sign up for a free trial and schedule a call using the form on the right, or directly at manta@getmanta.com

MANTA 4 Insurance

After introducing “MANTA 4 Finance”, “MANTA 4 Healthcare”, and “MANTA 4 Telco”, we present the next part of our “MANTA 4 Industries” series. Read about the issues MANTA helps insurance customers solve in the article below.

After introducing “MANTA 4 Finance”, “MANTA 4 Healthcare”, and “MANTA 4 Telco”, we present the next part of our “MANTA 4 Industries” series. Read about the issues MANTA helps insurance customers solve in the article below.

Regulatory Compliance and GDPR

It can be said that the regulatory requirements in terms of data protection for this industry are even more strict than in other industries. The companies’ systems contain large amounts of sensitive personal data that, as we now all know, has to be safeguarded with extra care. The General Data Protection Regulation (GDPR) threatens companies with astronomical penalties for noncompliance.

Big problems can also arise from an inability to accommodate the fundamental rights of data subjects (right to access, right to erasure, right to restrict data processing, etc.).  In these cases, the company has to show the supervisory authority exactly how it secures its data. 

In the worst-case scenario, if there would happen to be a data breach, the insurance provider would have to prove that it did everything humanly possible to stop it! Data lineage is a way of showing that, by drawing out an end-to-end map of the dataflows and all their movements within the BI and analytics environment.

Dynamic Insurance

One of the problems that the health insurance industry is facing, which most people outside of it fail to see, is the dynamic pace at which the industry is currently moving. It is not just about long-term insurance plans or car insurance. As people tend to engage in last minute and other forms of impulse travel, together with a growing demand for short-term nonstandard insurance such as for adrenaline sports and other activities, insurance companies have to be able to give their customers real-time access to their services.

If you take into consideration the amount of already-existing data that is needed to meet industry demands for fast analytics and calculation capabilities, this is almost impossible to achieve manually. Tools like MANTA come in as a must to allow companies to keep up with such a fast pace.

IoT & Insurance

With IoT slowly creeping into every industry, the insurance industry is no exception. Networks of connected sensors among household appliances and devices would be able to regulate the amount of electricity that is being used in the home, autonomously control a building or home’s energy consumption, and optimize energy intake. On a bigger scale, this can be used not only for utility companies but also to calculate and adjust house and property insurance needs.

Safe Zone

Insurance companies are all about keeping you safe and giving you assurance. What MANTA does for insurance companies is assures them that their data is being used to the fullest, and it effectively protects them in case of compliance needs or data breaches.

Do you have some questions about how to use MANTA in another industry? Book a call with one of our pre-sales experts using our bot or write us directly at manta@getmanta.com

MANTA 4 Telco

After introducing “MANTA 4 Finance” and “MANTA 4 Healthcare” in our new “MANTA 4 Industries” series, we are now moving on to another industry that MANTA is very familiar with. Read about the issues MANTA helps telecommunications customers solve in the article below.

After introducing “MANTA 4 Finance” and “MANTA 4 Healthcare” in our new “MANTA 4 Industries” series, we are now moving on to another industry that MANTA is very familiar with. Read about the issues MANTA helps telecommunications customers solve in the article below.

Data is Gold

For most companies in telecommunications (before and after GDPR), data is a huge part of their business. But usually not such personal data as with healthcare patients, rather data about past and current subscriptions, tariffs, and packages that clients have been enjoying as well as phone numbers—both as a product and as a way to engage with customers for advertising purposes.

Apparently, business mergers and acquisitions, as well as database acquisitions, happen quite often in this industry. As a result, several of MANTA’s customers from the telco industry have sought MANTA’s help after running into problems caused by having one too many databases on hand.

Prior to such mergers, each company has its own DWH filled with unique and valuable data. Therefore, as part of their growth and data migration plans, it is necessary to consolidate. Other data governance solutions often cannot handle such large databases or automatically read them in a reasonable amount of time. That is why customers implement MANTA to map the part of their environment that is invisible to their data governance solution as well as to make the entire process of gathering data lineage faster and more effective.

Thanks to MANTA, the entire process of data migration and consolidation happens much faster than it normally would and with complete control over all the data being transferred, which prevents any errors or problems from occurring. And as a bonus, the next time the customer makes an acquisition, it will be much easier for it to merge the other company’s data into its system.

Data Anonymization

However, the data the companies store may still be subject to regulations, at least to GDPR. That is why many companies need to proceed with data anonymization. The subject of data anonymization, personally identifiable information (PII), consists of data elements that alone or in combination can directly or indirectly lead to the identification of a specific individual.

Companies must identify the various locations where sensitive or noncompliant data is being stored as well as discover the relationships between this data. Not all records are equally sensitive; not all need to be anonymized. Sometimes, only parts of the data need to be re-written. (For example, a name and a country code in the same table will most likely not lead to the identification of a customer, but adding a city name could end up leading to quite precise identification.)

Using MANTA, you can construct and analyze metadata models that will identify PII in any component of your BI and analytics solution.

Do you have some ideas about how you could use MANTA in your industry but want to discuss your case with one of our pre-sales experts? Don’t hesitate to book a call using our bot or write to us directly at manta@getmanta.com

MANTA 4 Healthcare

After introducing “MANTA 4 Finance” as the pilot segment of our new “MANTA 4 Industries” series, we are moving on to another industry that MANTA is very familiar with. Read about what issues MANTA helps its healthcare customers solve in the article below.

After introducing “MANTA 4 Finance” as the pilot segment of our new “MANTA 4 Industries” series, we are moving on to another industry that MANTA is very familiar with. Read about what issues MANTA helps its healthcare customers solve in the article below.

Regulatory Compliance and GDPR

It can be said that the regulatory requirements in terms of data protection for this industry are even more strict than in other industries. The companies’ systems contain large amounts of sensitive personal data that, as we all know now, has to be safeguarded with extra care. The General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA) threaten astronomical penalties for noncompliance.

A big problem may also arise from an inability to accommodate the fundamental rights of data subjects (right to access, right to erasure, right to restrict data processing, etc.).  In these cases, the company has to show the supervisory authority exactly how it secures its data. 

In the worst-case scenario, if there would happen to be a data breach, the healthcare provider would have to prove that it did everything humanly possible to stop it! Data lineage is a way of showing that, by drawing out an end-to-end map of the data flows and all their movements within the BI and analytics environment.

Data Anonymization

Some of the consultancy companies that MANTA works with have recognized that the biggest struggle regarding GDPR compliance is most likely tracking customer data across multiple databases. The subject of data anonymization, personal identifiable information (PII), consists of data elements that alone or in combination can directly or indirectly lead to the identification of a specific individual.

Companies must identify the various locations where sensitive or noncompliant data is being stored as well as discover the relationships between this data. Not all records are equally sensitive; not all need to be anonymized. Sometimes, only parts of the data need to be re-written (e.g., a name and a country code in the same table will most likely not lead to the identification of a customer, but adding a city name could end up leading to quite precise identification).

Using MANTA you can construct and analyze metadata models that will identify PII in any component of your BI and analytics solution.

IoT and Healthcare

With all of the abovementioned regulations, healthcare is one of the most monitored industries in the world, and for good reason! It will only get harder to comply with these regulations, especially with the desire to digitalize all customer records and add IoT concepts that integrate data from wearable sensors. These wearables usually sync data in real time as well, giving doctors the ability to remotely monitor patients. This makes them a real-time security threat for medical experts, doctors, insurance providers, you name it! (Hence the possible data breach threats mentioned above.)

Conclusion?

The complexity of today’s BI and analytics environments makes it almost impossible to search for these relations manually. Luckily, MANTA can automatically analyze all database objects and data processing logic within your database, and if an additional description about the level of sensitivity of each record is provided, it can identify the locations of sensitive records. Then you can eliminate all potential threats to compliance as well as make sure you didn’t fail to find a complete record of customer data.

Do you have any questions for us, or do you want to read one of our case studies regarding this industry? Then hit us up at manta@getmanta.com and we will gladly reply! 

MANTA 4 Finance

MANTA is a solution for companies that have loads of data: huge, complicated data warehouses. But are you wondering how exactly MANTA fits into the data warehouses of big financial institutions? Welcome to our series called MANTA for Industries: Finance.

MANTA is a solution for companies that have loads of data: huge, complicated data warehouses. But are you wondering how exactly MANTA fits into the data warehouses of big financial institutions? Welcome to our series called MANTA for Industries: Finance.

Credit Risk Scoring

Financial institutions that offer consumer loans invest a lot of money, effort, and know-how from years of experience into the development of advanced credit scoring models. In most cases, only a few people in the organization know and have access to these algorithms.

One way to decode a credit scoring model is to collect a significant amount of customer data where credit scores are combined with variable credit factors and then use statistical methods to understand the model. These “dangerous” combinations of data are often present in BI solutions and data warehouses. Every BI solution should allow the separation of access to such data by properly categorizing data sensitivity and by enabling user entitlement setup. This is not easy to achieve, and it is especially difficult to verify if the setup is correct.

With MANTA, you can easily identify and visualize the components of BI solutions (for example, data marts) where unwanted combinations of such sensitive data are present, or you can analyze user data-access setup to see if there are direct or hidden and indirect ways to retrieve those data sets.

You can export lineage from MANTA that can then be used for BI security improvements. And you can even restrict the use of MANTA’s data lineage right in our native visualization. When you find such relations, you can then take them into account when setting up user access for different user groups and teams who have access to MANTA and monitor who has access to different parts of the lineage from different data marts.

Regulatory Compliance and GDPR

Another popular way to use MANTA in big banking institutions is to produce proof for internal auditors that your credit scoring models are well protected. With the enormous number of banking regulations as well as regulations such as GDPR, it is twice as important to have decent data lineage to show the auditor when he arrives. To learn more, read our GDPR article. (link)

GDPR has introduced many more threats pertaining to corporate internal data. For example, a customer may come and request that you honor one of his rights such as the right to be forgotten. In this case, you may need to use MANTA to find every single place in your company data marts where the customers data is being stored to make sure you delete every single one of those instances.

You may also need to anonymize data. And after using MANTA to find all the places where your data needs to be anonymized, you might want to use MANTA again to double check that there is really no way to identify that person.

Legal Threats

Being able to keep track of your environment and changes in your credit scoring algorithms is beneficial for many different reasons. One of our favorite client stories is about a customer who attempted to sue our client for not approving his loan the first time he applied, only to be approved a year later.

Using MANTA, the client was able to automatically find the changes made to the scoring algorithms over the last couple of years and identify the change in the algorithm for calculating credit scores for loans. The ability to show exactly what had changed and when allowed the financial institution to win the court case, saving them billions of dollars.

And how could you use MANTA in your financial institution?

Any comments or questions? Let us know at manta@getmanta.com, or go ahead and schedule a meeting using the form on the right.

 

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