How can CluedIn help?

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

1-1-1

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

Involving the business

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

2

What is the difference between the Data Warehouse and CluedIn

Clearing things up

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

What type of Data Catalog do you really want

Are there more than one?

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

4

Why DataOps and DevOps will converge

Data will obviously need care

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.

5

Why is my Data Lake not working

Involving the business

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

6

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

It happens everywhere

We talk through some of the reasons why data is so hard to consume across your business.

7

Why do I not trust our company data

It's a long story

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

8

One data platform to rule them all

It doesn't exist

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

9

Why is streaming interesting for my business

Why pull, when you could push?

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

How does the CluedIn merging engine work

Why is it breakthrough?

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

11

Where do I fix my dirty data

Here? There? Everywhere?

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

12

What is connected data and why is no one doing it

It's the only way

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

The idea of a Universal ID

Can it exist?

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

14

Why don’t you have timely access to data

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

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

15

The Problem with the In-Memory Trend

Every cloud...

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

16

Why have I never achieved the 360 view of our customer

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

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

17

I have 1000 systems to integrate help

Impossible?

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

18

Data quality metrics

What does it all mean?

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

19

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

What do I need?

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

20

Data Maturity Model Frameworks

Where are you?

We talk through the different stages of data maturity.

21

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

Cloud First

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

22

How to Enable Public Datasets?

There is a plethora of public data available.

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

GraphQL vs SQL

The new data language

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

Why FinOps is important for your data foundation?

Cost Management...Managed.

FinOps is a critical part of your Data Foundation.

25

Understanding Data Lineage

Data Lineage is so much more than Wikipedia tells us. 

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