How can CluedIn help?

These white papers will help you build your use case for solving your challenges with CluedIn.

1-1-1

Involving the business

How does the Data Steward and Data Citizen play a role today

We talk through how business users can play a role in the data management lifecycle.


2
Clearing things up

What is the difference between the Data Warehouse and CluedIn

There are many technologies that play a role in your data landscape. In this white-paper we cover how we compliment the Data Warehouse.

3
Are there more than one?

What type of Data Catalog do you really want

We talk through the different evolutions of data catalogs and how technology may obsolete what you think you want in a data catalog.

4

Data will obviously need care

Why DataOps and DevOps will converge

Without a doubt, data requires the same care that our applications and infrastructure does. In the future we will deploy data like we do code.

6
It happens everywhere

Why does it take me so long to get data at work

We talk through the different evolutions of data catalogs and how technology may obsolete what you think you want in a data catalog.

5
Involving the business

Why is my Data Lake not working

The industries reaction to the limitations in the Data Warehouse was to the complete opposite.


7

It's a long story

Why do I not trust our company data

The path to usable data is long and treacherous, we give the reasons for why you don't trust the data you have.

8

It doesn't exist

One data platform to rule them all

Your data landscape will adapt, change and evolve over time. There is not one platform for everything.

9

Why pull, when you could push?

Why is streaming interesting for my business

Do you sit there and refresh your email every 5 seconds? No, it gets pushed and alerted to you. We should do the same with data.

10

Why is it breakthrough?

How does the CluedIn merging engine work

We have been deduplicating data the same way since the dawn of MDM. Most take a very naïve approach to solving it.

11

Here? There? Everywhere?

Where do I fix my dirty data

There are different benefits that are gained from cleaning data at source, in a unified platform and on use.


12

It's the only way

What is connected data and why is no one doing it

Data is not relational, it is a network of relationships. Why is it so important to give your data the best chance it has to bring value?

13

Can it exist?

The idea of a Universal ID

We have all attempted it before - to produce a universal ID for a record. Why did it not work and cannot work?

14

It's right there, why can't we use it?

Why don’t you have timely access to data

Data needs a lot of care before we get it to the point where it is usable.

15

Every cloud...

The Problem with the In-Memory Trend

In-Memory databases are solving huge challenges. They also have their own flaws.

16

We have all tried it, but why does it fail?

Why have I never achieved the 360 view of our customer

Think about it. You have probably attempted this type of project many times before. Why did it fail?

17

Impossible?

I have 1000 systems to integrate help

Traditional data integration approaches make it impossible and impractive to achieve a company-wide view of your data.

18

What does it all mean?

Data quality metrics

Seeing scores of data quality don't mean a thing unless you can explain the scores.


19

What do I need?

What resources and process do I need to make a Data Foundation a success

A Data Foundation is so much more than just technology. We talk through all the pieces of the puzzle.

21

Cloud First

Why is a Cloud-Native Master Data Management platform important?

A Cloud Native Master Data Management system is key to the success of modern MDM needs.

20

Where are you?

Data Maturity Model Frameworks

We talk through the different stages of data maturity.



22

There is a plethora of public data available.

How to Enable Public Datasets?

Many firms have cataloged and indexed the datasets to make it relatively easy to find and discover. The challenge with taking two discrete datasets and blending them is that most datasets don't connect point to point like this.

23

The new data language.

GraphQL vs SQL

In effect, GraphQL is a language that relies on different parts of the query not only running against different sources, but the result also potentially being composed from many sources.

24-1

Cost Management...Managed.

Why FinOps is important for your data foundation?

FinOps is a critical part of your Data Foundation.


25

Data Lineage is so much more than Wikipedia tells us. 

Understanding Data Lineage

At its core, Data Lineage is the transparency and visibility over the journey of data as it
flows throughout your business.


26

Your transactional and unstructured data needs attention to!

Does Unstructured and Transactional Data Make Sense for MDM and CluedIn?

We walk through the cases where unstructured and transactional data makes complete sense to put into your MDM system.

27

Deciding what data to Master can be tricky.

What Data do I Send to CluedIn?

This guide will take you through some of the extra choices you have for processing data in CluedIn.


28

Discover why Graph is key to your next MDM implementation.

Why is Graph "key" to the Modern MDM Movement?

This whitepaper details why thinking in Graph for your MDM is key to a modern data stack.

29

Why is now the time to implement MDM?

Justifying an MDM project to the business

The key to unlocking the value of your data is to make sure that you are delivering the highest quality, governed, integrated data to the edge of the business.

Wanting to dive into the detail?

Let's hook you up with a data expert to see if there are more answers you need.