Manta Business

Why All IoT Projects Need Data Lineage

April 17, 2018 by

The rapid growth of IoT (Internet of Things) devices and their associated data streams brings with it a completely new discipline of data. The huge amount of data that companies have to process (and store!) from these projects is complicated, dynamic, and usually of a very sensitive nature, so it has to be handled with care. To process such a large amount of data in an effective way, we need to automate the metadata harvesting, and we need to be able to get complete end-to-end data lineage in order to trust our data. So, keep reading. Here are a couple of MANTA x IoT use cases we have drafted for you!

The rapid growth of IoT (Internet of Things) devices and their associated data streams brings with it a completely new discipline of data. The huge amount of data that companies have to process (and store!) from these projects is complicated, dynamic, and usually of a very sensitive nature, so it has to be handled with care. To process such a large amount of data in an effective way, we need to automate the metadata harvesting, and we need to be able to get complete end-to-end data lineage in order to trust our data. So, keep reading. Here are a couple of MANTA x IoT use cases we have drafted for you!

IoT & Smart Homes

There are buildings that can collect information about their neighborhoods as well as smart homes that connect appliances to mobile phones – monitoring your fridge and adding groceries to your shopping list, heating your rooms and plenty of other activities that make up your daily life – this is the concept of a smart home. But then at the end of the day, you have a bundle of very personal information about your customers’ lives that is all collected in a company DWH and/or in a “cloud far, far away”. This data will come with the need to comply with regulations for personal data. This could be compliance with GDPR or even HIPAA in some cases, if the data includes information that could indicate the customer’s health status (e.g. if the home is barrier-free, there is a special medication device installed, what food is in the fridge).

IoT & Healthcare

With HIPAA and other 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! 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 as well.

IoT & Finance

IoT can be incorporated into the finance industry through a broad variety of payment methods, virtual payment methods, apps, microchip technology, cards, sensors, and so on. The data collected from these payment methods can also be used, for example, to calculate individualized rates for term-based insurance or other financial products/services that can adapt to a person’s real-world behavior rather than an estimated mathematical model. But, as if companies working in finance didn’t already have enough data, all of these concepts dramatically increase the content of company data warehouses.

IoT & Retail

IoT locating technologies and on-product sensors could enhance the customer shopping experience by sending instant personalized promotions, sharing reviews from other customers, and offering remote payment options. A future model could offer a hands-free shopping process, and even current ones would also be able to track customers’ moves through the aisles, their ideal “shopping path”. Microchips or sensors inside goods could also help the company create an automatic on/off -stocking process, which would leave the company to deal with a never-ending flow of new information into their data warehouses.

IoT & Utilities

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 intake. On a bigger scale, this should also help optimize large-scale energy grids.

Conclusion: IoT & Data Lineage

IoT is a data-driven concept, and all data-driven concepts have exactly the same problem: their data needs special attention! That includes precisely tracking their data as well as having complete end-to-end data lineage that is, preferably, completely automated – because the amount of data that floods company DWHs after implementing an IoT solution is insane! And no company has the kind of time and employees necessary to manually reconstruct data lineage from that many sources, right?

MANTA can enable your company to prove exactly where your data is, where it is going, and how it is treated along the way. This can mean the difference between complying with a regulation, gaining a happy customer – or putting your data at risk. Although living on the edge is exciting, that does not apply to your data, ever!

Ready to learn more? Leave us a note in the form or let us know via email at manta@getmanta.com.

 

Spring Clean Your DWH!

March 29, 2018 by

Yes, it’s time for some spring cleaning! Some of us might have to deal with GDPR soon, some of us want to optimize our DWHs and save money as well, some of us want to start with agile development, and some just want to migrate to the cloud! No worries, read on and see how MANTA can help.

Yes, it’s time for some spring cleaning! Some of us might have to deal with GDPR soon, some of us want to optimize our DWHs and save money as well, some of us want to start with agile development, and some just want to migrate to the cloud! No worries, read on and see how MANTA can help.

GDPR

With GDPR, you need to address at least three areas related to physical persons – understand 1. what data you have; 2. where it is stored; 3. if you have consent to use it for a specific purpose; and what you are using the data for. Getting a complete understanding of which systems the person/related data elements are distributed, stored and used in is traditionally a lengthy and expensive process. However, items #2 (where your data is stored) and #4 (how you are using the data) are automated when you use Manta. This way you get an understanding quickly and, even more importantly, MANTA keeps that information up-to-date.

Migrating to the Cloud

When migrating your DWH to cloud technology, you need to be careful about what exactly you are migrating. For example, if you are Migrating Microsoft SQL Server to Azure, you are paying twice – once for the processing units (cDWUs), and once for the storage (DWUs). In this case, you want to make sure that you are transferring/migrating only what you need.
Your data warehouse, that has been developed over the last several decades, may (and likely does) contain obsolete or legacy parts that have not been used in a while or have even been decommissioned. MANTA can map your DWH and see which pieces of data are being used and which not.

Note: Even if you’re not migrating to the Cloud, you can still benefit from cleaning up the legacy or obsolete parts of your DWH. By removing the unused parts of your data warehouse, you may not only save on licenses by reducing the size of your DWH, but also reduce your operational costs (by not maintaining unused parts) as well as reduce the risk of using outdated or invalid data in the unused part of the warehouse. Automating such analyses gives you an immediate understanding which leads to immediate savings.

Sensitive Clouds

When you want to save space in your on-premise DWH by migrating some parts to the cloud but are afraid of security issues, you can always migrate only part of your warehouse. For example, MANTA can scan for all tables that are related to tables of sensitive data and show you where those data elements are being propagated and used. Then you can migrate only less sensitive data and save DWH space without losing your security status.

Sandboxing a Cloud

Another common use case in data migrations is when someone is trying to create a sandbox. You want to let a third party develop for your environment but don’t want to give them access to the entire environment, just a small part – in a copy! But first you need to find out exactly which records in your DWH are connected to your product so you don’t give too little or too much. This could take many hours, or even days, depending on your environment. But thanks to MANTA, you can automatically scan the data in a few minutes and identify the relevant pieces.

Data Lineage: The Penguin Effect

February 23, 2018 by

One jumps, they all jump! The penguin effect is a cute term from crowd psychology that suggests that penguins (and humans too, apparently) wait for one “victim” to start doing something, and then they all join in. We don’t know who was first, but now they’re all in—in data lineage!

One jumps, they all jump! The penguin effect is a cute term from crowd psychology that suggests that penguins (and humans too, apparently) wait for one “victim” to start doing something, and then they all join in. We don’t know who was first, but now they’re all in—in data lineage!

There is no doubt that the importance of data lineage has grown enormously over the past couple of years. For example, the number of searches on Google for “data lineage” has doubled in the past year, and quadrupled since 2014! Simultaneously, the term “data lineage” has been appearing in a significant number of academic papers and scholar projects each year.
We are proud to say that the longing for data lineage has been reflected in our numbers as well. The featured image is a map of every use of the MANTA Flow demo. It shows that MANTA has been attracting businesses, partners and customers on all six continents and in more than 80 countries—from Vancouver to Wellington, from Santiago de Chile to Tokyo!

Let’s take a closer look at the evidence here

We took data from the past 3 years and spread them on the map. Naturally, most of the inquiries have come from the United States—almost exactly a third of them. Second place goes to India. We can’t be surprised about that one either! There isn’t really any special trend in the statistics. It just seems that 2015 kicked-off with a couple of inquiries from Riyadh, followed by the US boom. Part of the success is, of course, thanks to our hard-working marketing team (side note: this article was written by its hardest-working member), but we would have to do a really in-depth analysis to find out how much.

All in all, out of all the 8.2K connections, more than three quarters are from 2017! We can, of course, describe this as proof of the rapidly growing popularity of MANTA and, perhaps even more importantly, of the widening of MANTA Flow’s scope—the capabilities of the product (the increasing number of technologies analyzed). Also, we can’t overlook the impact of our partnerships. 2017 was big in this sense, too.

Yes, as demonstrated by this article, data lineage has seriously caught the attention of enterprises all over the world. Now, more than ever, companies rely on having their data under control.

Do you have your data under control, or does your data control you? manta@getmanta.com.

A Tech Support Love Letter: Be Our Valentine!

Valentine’s Day is heading our way and we know who our Valentine will be, but do you? We’ve made you this card so you can see how our customers get nothing but love and affection from MANTA’s support and development teams. It’s a love letter in numbers, enjoy!

Valentine’s Day is heading our way and we know who our Valentine will be, but do you? We’ve made you this card so you can see how our customers get nothing but love and affection from MANTA’s support and development teams. It’s a love letter in numbers, enjoy!

With love, MANTA.

A LOVE LETTER IN NUMBERS

The Year of MANTA and Why We’ve Published Our Pricing Online

December 31, 2017 by

We’ve seen a massive surge in the world of data lineage over the last year.  More buzz, more leads, more customers for us and (from what I’ve heard) for other metadata players as well. It might come as a bit of a disruption, but we’ve decided to do something which is very common in other industries, but not in ours. We’ve published our pricing online. Why?

We’ve seen a massive surge in the world of data lineage over the last year.  More buzz, more leads, more customers for us and (from what I’ve heard) for other metadata players as well. It might come as a bit of a disruption, but we’ve decided to do something which is very common in other industries, but not in ours. We’ve published our pricing online. Why?

The Year We’ve Come Through

2017 is coming to an end, and so it is the right time to take a look back. It was a very hot year for metadata and data governance. Partially thanks to the new GDPR regulation, but there are more reasons behind it – more and more enterprises have come to the understanding that the only way to build an efficient data-driven company is through proper data governance. In 2016, data got a lot of attention, how big it is or can potentially be, how to manage large volumes, velocity, and variety in data.

In 2017, we all started to realize that it is not just about data, but also a lot about data algorithms – the way your data is and how it’s gathered, transferred, merged, processed, and moved around your company. Thanks to GDPR, internal discussions have been initiated about how and where sensitive / protected data elements are used, and suddenly, it turns out that we are flooded not just with data but with data algorithms too, and it is impossible to handle it all manually without automation.

That has drawn even more attention to MANTA and its unique data lineage automation capabilities. Our website basically exploded – our audience doubled and the use of our live demo nearly tripled. We have on-boarded several amazing new customers from all around the world, and we delivered four major releases this year, with plenty of new features in all of them including Public & Service APIs and new technologies (SSIS, IBM Netezza, IBM DB2, and Impala, to name a few). Simply said, 2017 was a fantastic year and more is coming in 2018!

And even though this year was yet another giant step for MANTA, we decided to do one more thing that will shake things up. We’ve done something that’s pretty common in all the other industries except ours.

Yes, we’ve published our pricing online for everyone to see.

And why?

MANTA is taking the lead in transparency and openness

Sometimes there are good reasons for hiding the price of your product or service. And it is common practice in the enterprise software industry. But does that really make sense? Let’s take a look at the usual reasons, then:

1) You might be legally bound to hide the price by a government or its suppliers. Yes, national security is a serious issue, and there might be some limitations put on companies which deal with it. But that works only for individual deals and is hardly a reason to hide the price.

2) You want to participate in tenders with secret bids. Yes, that also makes sense – especially when you are dealing with clients that focus only on the price. You would not want to lose just because your bid is a few thousand higher, would you? Perhaps not, but this is not our case – MANTA is a very unique software product with clear and easy to see value for its users. The price has to be reasonable, but it is rarely a way how to win anyone’s business.

3) You want to keep everybody in the dark. Yes, some do want that. But frankly, it’s a rather dishonest strategy. It’s foolish to expect that customers do not know other players on the market and their prices. It’s even more foolish to try to control the market by spreading rumors and making deals in the shadows.

When you are confident of your product and what it stands for, you are also confident of its price. There’s no reason to follow the “industry standard” by not disclosing the enterprise IT product prices. So dive into our pricing right here and if there’s something that needs clarification, just take a look at our pricing glossary right below it.

Thank you for your support this year and see you in 2018!

Yours,

Tomas

 

MANTA & Solidatus: Powerful Data Visualization Hand-In-Hand With Automation

October 25, 2017 by

Recently, devs from MANTA and techs from Solidatus have joined forces to bring data owners and analysts a powerful visualization and management tool for data lineage supported by an advanced automatic discovery application. Read on to find out more about our new friends and what this bond has to offer.

Recently, devs from MANTA and techs from Solidatus have joined forces to bring data owners and analysts a powerful visualization and management tool for data lineage supported by an advanced automatic discovery application. Read on to find out more about our new friends and what this bond has to offer.

Since its launch at the beginning of 2017, Solidatus has won long-term contracts with major global Financial, Pharma, and Utility companies. Solidatus is a powerful data lineage discovery and visualization tool that complements existing solutions such as Collibra, Informatica, IBM, Excel, and many others. With its easy to use, intuitive, and highly scalable web interface it sources and combines all the lineage information in one place.

In partnering with MANTA, Solidatus will build on its proven success creating data models across end-to-end business flows by integrating with MANTA’s database scanning and cataloging technology. This will enhance the discovery and management of complex flows hidden deep in databases, scripts, stored procedures, and other kinds of data processing logic.

Here are some of the perks of our partnership:

  • Data lineage solution incomparably faster than any other manual discovery app
  • Collect metadata from structures like programs, applications, and ETL workflows
  • Powerful visualization of metadata across end-to-end business processes
  • Ability to validate, edit, and add business terms and additional metadata
  • Share read only models with anyone in the business
  • Intuitive web interface which allows users to incrementally build and assign metadata models
  • Collapsible filters as well as customizable searching and querying
  • Enhanced data governance, risk modelling, and project management tooling
  • Accelerated discovery of low level lineage through crowdsourcing metadata from a full system audit, version control, and visual temporal comparison
  • Support for systems migration, integration, and transformation
  • Deep insight into data for MiFID, BCBS 239, NYS DFS 504, GDPR, and FRTB
  • Custom data models that consider the organization structure, complexity, controls, and governance requirements

Learn more about Solidatus on their website or just ask for our joint solution on manta@getmanta.com.

So, You Are Planning a GDPR Solution without Data Lineage?

September 21, 2017 by

How complete data lineage can help you with GDPR compliance projects. Or, more precisely, how they cannot survive without it. 

How complete data lineage can help you with GDPR compliance projects. Or, more precisely, how they cannot survive without it. 

For the last couple of months, anytime I open my browser, it’s all over the internet! GDPR everywhere. Our partners and customers see it the same way and often come to us asking what role data lineage from MANTA plays in this whole GDPR boom. Let’s have a look.

The General Data Protection Regulation (GDPR) takes effect on May 25th, 2018. So it’s about time to find out if this regulation affects you or not. The GDPR will apply to any company that stores personal information of EU Citizens, so chances are this is your company as well. And because the fine is up to €20 million or 4% of the company’s revenue (whichever amount is higher), we all might want to avoid paying that money.

Data Lineage for the GDPR?!

Although data lineage by itself won’t make you compliant (you still need a Certified Data Protection Officer (DPO), consent from EU citizens in your database, and a “few” other things), it can solve a large portion of your GDPR worries.

End-to-end data lineage can give you overall insight into ALL of your data. Here are the things that quality data lineage can tick off your 20-something-long GDPR to-do list:

1. Know your data: The GDPR requires you to know not only were data is being stored, but why, how, and when it has been shared with other systems, both externally and internally. This includes knowing where your data is, where each record in your CRM or business database comes from, and where it is held in your data warehouse.

Luckily for you, MANTA can crunch all the SQL code in your database and with the provided custom mapping, make not only a technical, but also a business data lineage map so anyone can swiftly maneuver through it.

2. Give individuals the “right to be forgotten” (RTBF): This is something anyone can request from your company as of May 25th, 2018. You must comply without delay, and certainly within 30 days. (Source) But how are you going to do that when you know you have your customers data scattered across different databases? Data lineage from MANTA can take you back to all the records where your customer’s data is being stored so you can be sure that you have erased it from all the records.

3. Data portability for everyone: Anyone can also request a copy of all their data stored by your company. (Source) ALL their data, including stored e-mails, purchasing and payment history from different databases, and so on. With full data lineage, you can much more effectively allocate your resources and save money on developing such solutions.

Better Safe Than Sorry

If you are struggling with the GDPR and trying to find a way to prep your company as much as possible so that you are in the safe zone when the GDPR takes effect, data lineage is something you should definitely consider getting yourself. An average implementation of  MANTA to your data warehouse usually takes one or two days. Depending on the length of your usual purchasing process, you might want to give us a call tomorrow, next week, or next month at the latest. Each company’s needs are different, and it’s better to start in time so you can be safe rather than sorry.

Not sure how it works? Try our online demo and make sure you know all supported technologies and 3rd party solutions. Any questions on how MANTA can be useful when complying with the GDPR? Just ask us at manta@getmanta.com!

A Metadata Map Story: How We Got Lost When Looking for a Meeting Room

September 1, 2017 by

You may think that I have gone crazy after reading the title above or hope that our blog is finally becoming a much funnier place. But no, I am not crazy and this is not a funny story. [LONG READ]

You may think that I have gone crazy after reading the title above or hope that our blog is finally becoming a much funnier place. But no, I am not crazy and this is not a funny story. [LONG READ]

It is, surprisingly, a metadata story. A few months ago, when visiting one of our most important and hottest prospects, we arrived at the building (a super large finance company with a huge office), signed in and passed through security, called our main contact there, shook hands with him, and entered their private office space with thousands of work desks and chairs, plus many restrooms, kitchens, paintings, and also meeting rooms.

The Ghost of Blueberry Past

A very important meeting was ahead of us, with the main business sponsor who had significant influence over the MANTA purchasing process. Our main agenda was to discuss business cases involving metadata and the role of Manta Flow. So we followed our guide and I asked where we were going. “The blueberry meeting room”, he replied. We stopped several times, checking our current position on the map and trying to figure out where to go next. (It is a really super large office space.) After 10 minutes, we finally got very close, at least according to the map. Our meeting room should have been, as we read it on the map, straight and to the left. But it was not! We ran all over the place, looking around every corner, checking the name printed on every meeting room door, but nothing. We were lost.

Fortunately, there was a big group of people working in the area, so we asked those closest to us. Several guys stood up and started to chat with us about where that room could be. Some of them started to search for the room for us. And luckily, there was one smart and knowledgeable woman who actually knew the blueberry meeting room very well and directed us to it. In 20 seconds, we were there with the business sponsor, although we were a few minutes late. Uffff.

That’s a Suggestive Question, Sir!

Our gal runs a big group, a business, and BI analysts who work with data every single day – they do impact and what-if analyses for the initial phase of every data-related project in the organization. They also do plenty of ad-hoc analyses whenever something goes wrong. You know, to answer those tricky management questions like:

“How did it happen that we didn’t approve this great guy for a loan five months ago?”

or

“Tell me if there is any way a user with limited access can see any reports or run any ad-hoc queries on sensitive and protected data that should be invisible to her?”

And I knew that they had very bad documentation of the environment, non-existing or obsolete (which is even worse) as do many organizations out there, most of it in Excel sheets that were manually created for compliance reasons and uploaded to the Sharepoint portal. And luckily for us, they had recently started a data governance project with only one goal – to implement Informatica Metadata Manager and build a business glossary and an information catalog with a data lineage solution in it. It seemed to be a perfect time for us with our unique ability to populate IMM with detailed metadata extracted from various types of programming code (Oracle, Teradata, and Microsoft SQL in this particular environment).

Just Be Honest with Yourself: Your Map Is Bad

So I started my pitch about the importance of metadata for every organization, how critical it is to cover the environment end-to-end, and also the serious limitations IMM has regarding programming code, which is widely used there to move and transform data and to implement business logic. But things went wrong. Our business sponsor was very resistant to believe the story, being pretty OK with what they have now as a metadata portal. (Tell me, how anyone can call Sharepoint with several manually created and rarely updated Excel sheets, a metadata portal? I don’t understand!) She asked us repeatedly to show her precisely how we can increase their efficiency. And she was not satisfied with my answers based on our results with other clients. I was lost for the second time that day.

And as I desperately tried to convince her, I told her the story about how we get lost and mixed it with our favorite “metadata like a map, programming code like a tricky road” comparison. “It is great that you even have a map”, I told her. “This map helped us to quickly get very close to the room and saved us a lot of time. But even when we were only 40 meters from our target, we spent another 10 minutes, the very same amount of time needed to walk all the way from the front desk to that place, looking for our room. Only because your great map was not good enough for the last complex and chaotic 5% of our trip. And what is even worse, others had to help us, so we wasted not only our time, but also theirs. So this missing piece of the map led to multiple times increased effort and decreased efficiency. And now think about what happens if your metadata map is not complete from 40% to 50%, which is the portion of logic you have hidden here inside various kinds of programming code invisible to IMM. Do you really want to ignore it? Or do you really want to track it and maintain it manually?”

And that was it! We got her. The rest of our meeting was much nicer and smoother. Later, when we left, I realized once again how important a good story is in our business. And understandability, urgency and relevance for the customer are what make any story a great one.

And what happened next? We haven’t won anything yet, it is still an open lead, but now nobody has doubts about MANTA. They are struggling with IMM a little bit. So we are waiting and trying to assist them as much as possible, even with technologies that are not ours. Because in the end it does not matter if we load our metadata into IMM or any other solution out there. As long as there is any programming code there, we are needed.

This article was originally published on Tomas Kratky’s LinkedIn Pulse.

HELP! How Can I Include OFSAA in My Data Lineage?

August 30, 2017 by

Lately, we have written a lot about how MANTA can help you comply with all kinds of regulations, but risk and compliance go hand-in-hand for our customers.

Lately, we have written a lot about how MANTA can help you comply with all kinds of regulations, but risk and compliance go hand-in-hand for our customers.

They often use a risk management tool called Oracle Financial Services Analytical Application (OFSAA) and ask us if MANTA works together with it. The answer is, YES! Read on to find out how to use MANTA together with OFSAA to really get the hang of risk management.

RISKY BUSINESS?

Let’s start with a story from the field. We use a credit card company in this example, but this story really does apply to a wide range of financial products. Our story starts with a customer who applied for a credit card, but the application was denied by the company.

Then he returned half a year later and applied again. The second time, he got it. But how was this possible? The credit card company then had to manually go through all the data and current calculations, and it took them months to find out what had caused the problem – during the 6 months between the two requests the financial company had changed the algorithms for calculating creditworthiness. So, being able to give the customer an explanation required a lot of work, stress, and time! Wouldn’t all of this have been much easier if the company had had MANTA?

DO IT THE EASY WAY…

How could the company have solved the problem using MANTA and OFSAA? MANTA provides information about stored procedures and data handling quickly and accurately. It not only provides data lineage but is able to compare current revisions with historical ones. Instead of manually going through all the past algorithm records, they could have had MANTA solve the problem for them automatically. The company could have easily looked at the algorithm used on the date the customer first applied in just a few clicks. And OFSAA helps MANTA effectively get all the information it needs.

OFSAA MAKES IT EVEN BETTER!

OFSAA works as a system above your Oracle database, using its logic to generate SQL codes. MANTA and SQL code are good friends, so it’s easy for MANTA to take the information about your financial services from OFSAA and add it to the data lineage. The outcome is detailed end-to-end data lineage that MANTA provides by parsing your Oracle database and adding mapping and OFSAA scripts. And the best part of it is that OFSAA and MANTA “speak” the same language, so the entire process is FAST, saving you time and money you can use – well, really on anything better than manually searching through scripts and stored procedures.

Don’t do “risky business”. Go ahead and fill in this form to get a free trial to have a look at MANTA yourself.

MANTA + Scalefree = Data Vault Heaven

August 15, 2017 by

We have an exciting announcement for all of you! MANTA has teamed up with Scalefree, and exciting things are headed your way! The guys at Scalefree are real pros at building information systems and data vaults, offering a full range of BI solutions.

We have an exciting announcement for all of you! MANTA has teamed up with Scalefree, and exciting things are headed your way! The guys at Scalefree are real pros at building information systems and data vaults, offering a full range of BI solutions.

Data Vault 2.0 is a system of business intelligence comprised of 3 (plus one) pillars that are required to successfully build an enterprise data warehouse system:

  • A flexible model: designed especially for data warehousing, the Data Vault model is very flexible, easy to extend, and can span across multiple environments, integrating all data from all enterprise sources in a fully auditable and secure model.
  • An agile methodology: because the Data Vault model is easy to extend (with near-zero or zero change impact to existing entities), successful projects choose the Data Vault 2.0 methodology, which is based on Scrum, CMMI Level 5, and other best practices.
  • A reference architecture: spanning the enterprise data warehouse across multiple environments and integrating batch-driven data, near-real-time and actual real-time data streams, and unstructured data sets.

Furthermore, the agile methodology also includes best practices for the actual implementation of the Data Vault model, for deriving the target structures (in many cases, dimensional models, but not limited to those), and for the implementation of the architecture. All implementation patterns have been fine-tuned for high performance over more than 20 years and successfully used to process up to 3 petabytes of data in a U.S. government context (defense/security).

While adapting better to changes than pretty much any other architecture, Data Vault is braced for “Big Data” and “NoSQL”. This provides the customer with the same level of efficiency, now and in ten years, erasing all worries about the rapidly growing amount of data in your business.

As one of Scalefree’s founders, Dan is now establishing his concept on the market. In the training, exclusively certified by him, customers can learn the why/what/how of Data Vault 2.0.

And where does MANTA come in?

When you want to build a truly perfect data vault model, having strong data lineage is essential. Complete end-to-end lineage gives you insight into the structure and all procedures inside your data warehouse. Now that you know exactly where your data comes from and what data flows it goes through to get all the way to the end table, you can create an accurate data vault model that is applicable in many ways.

Have we aroused your curiosity about how to build and use a data vault in your business? Then be sure to check out the Scalefree Data Vault 2.0 Boot Camps  and save yourself a seat. Upcoming training programs will be held in Brussels, New York City (with Dan Linstedt), Vienna, Oslo, Dublin, Santa Clara CA, and Frankfurt.

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