Starting Your Modern DataOps Journey

Tuesday, December 1st - Starting Your Modern DataOps Journey

In this webinar, we'll explore what "Data Ops" is, why should you consider it and how to begin your transition to a DevOps and DataOps-style of work.

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More Guides

Guides & White Papers

A Guide to Migrating Data Workloads to the Cloud

The Cloud Is Not As Magic As They Want You To Think

Building Large Scale Data Migration Frameworks

How to Bridge Data Models and IT Operations for Simpler Compliance

Data Integration Software

The Buyers' Guide to

Architecting Systems For Effective Control Of Bad Data

Your Guide to Enterprise Data Architecture

Designing Data Applications The Right Way

Data Migration for Humans

What makes a data migration successful?

Data Modeling and Data Integration

The Guide to Data Migration Projects

Data Migration for Humans

Conquering Challenges Of Data Anonymization

The Guide to AnaCredit

10 Things You Need to Know about AnaCredit

Moving from on-premise to cloud can be complex. This guide walks you through what you need to know, and the pitfalls to watch out for.

Download now and learn:

  • How to guard against costs creeping up unnoticed
  • Why estimating pricing is so hard (and how to understand your costs)
  • Why and how to deal with multiple clouds
  • Tips for choosing a cloud vendor
  • Some tips on optimizing performance - from people who've done it

When managing large-scale data migrations, often with multiple legacy systems, the traditional approach means the repetitive effort grows with the project scope.

But with a repeatable framework approach that automates much of the simple work, you get faster results and significant cost savings.

Download now and find out:

  • How an iterative, repeatable and transparent approach can work for your data migration
  • Why it’s important not to actually touch any data by hand
  • How an automated framework frees engineers’ time so they can focus on solving the hard problems

If you're struggling to meet stringent regulations such as Basel II or MiFID, automating the translation of these models can help you obtain a single, standardized version of the truth and provide a trusted link between documentation and production systems. 

Download now and find out:

  • How siloed data and fragmented institutional knowledge lead to hefty reconciliation costs and complicated dialogue with regulators.
  • The benefits of 1:1 conversion between your data models and IT operations
  • How our client used the CloverDX Data Bridge to build a clear and repeatable auditing process 
  • The importance of capturing everything in the initial modelling process

Looking for data integration software but not sure where to start?

Start with our Buyers' Guide.

This guide walks you through everything you should be considering when choosing the right software for your business - from how to identify your organization's needs and capabilities to planning for the future and tips to get the most out of a demo.

Read now and discover what you need to be asking potential vendors.

 

Bad data is unavoidable. But you can (and should) design your data processes to manage that bad data effectively.

Read the white paper to discover:

  • Best practices for automated error handling
  • How to involve business users in error management
  • How reporting can help auditing and process improvement

 

Is a data warehouse or a data lake the best option for your business?

Or is your best choice for enterprise data architecture something different?

This white paper looks at what each option involves, and the advantages and disadvantages of data warehouses, data lakes, data vaults, data hubs, data marts and more. 

Does your business handle data with an Excel file full of formulas and macros, being exchanged over email between people who don't really understand how it works?

If this approach is becoming unsustainable and error-prone, read this white paper to learn a better way.

Download and discover:

  • The importance of building in a separate data integration layer
  • How to separate the business logic from the data itself
  • How a data integration layer can speed up development, improve access to data and future-proof processes.

If you're facing the prospect of a data migration, this e-book will help you understand how to prepare and plan for a successful project. 

Download the e-book now and discover:

  • The danger of thinking a data migration is 'just an IT project'
  • How to minimize complexity
  • The importance of building in repeatability from the start

Data models provide a graphical, intuitive way for both business and technical stakeholders to visualize complex data structures and relationships.

But data models have historically required development effort to turn them into actionable code. 

The CloverDX approach can help automate this process.

Bringing data models and data integration together can improve collaboration between business and IT, speed up time to production and turn data models into ETL jobs at the click of a button.

Download the Guide to Data Migration Projects and discover the 13 stages involved in a migration, and the best practices to make each one a success.

The guide will show you:

  • How to scope your project properly
  • Why data discovery should be done before your budget
  • How to plan and work with understandable milestones
  • The importance of building an iterative data migration process

Getting high-quality test data can be a real challenge when it comes to testing. 

Synthetic data can never represent the same use case coverage and quality as real production data. But using production data can risk violating security or privacy policies. 

This white paper outlines how you can anonymize production data effectively to get the best possible data for testing.

10 Things You Need To Know About AnaCredit

AnaCredit (The Analytical Credit and Credit Risk Dataset), is a project from the European Central Bank (ECB) to create a shared database containing information on bank loans to companies. Credit institutions across the Eurozone will be required to report specific, standardized data on loans and other credits.

This e-book answers 10 key questions about AnaCredit and explains how to prepare for its data demands.

Webinars

Processing Large Data Volumes with CloverDX Cluster in the Cloud

37.21

Supporting Data Ops dashboard in CloverDX

47.23

Loading Data Into A Cloud Data Warehouse (Redshift/Snowflake)

41.22

From Old School Data Pipelines to DevOps and DataOps

46.01

Formula 3 Group: Staying Small And Agile While Working With Large Enterprise Ecosystems

48.21

Why automation is better than Excel data manipulation

42.03

It's time to ditch your homegrown ETL. It doesn't have to hurt.

38.45

Building elegant processes for mapping unwieldy complex data structures (JSON, XML, HL7)

42.37

Surviving a Data Migration

31:08

Bridging Legacy Banking and Agile FinTech with Choice Bank

57.43

Data Ingest For Faster Data Onboarding

50.06

Working with stubborn REST APIs

48.53

Running CloverDX In The Cloud (AWS & Azure)

49.53

Building APIs and User Interfaces For Your Data Workloads

25.57

Deploying ETL To The Cloud

53.48

Migrating Data Workloads to Cloud

53.02

Repeating Data Migrations to Workday

49.56

Give Data Owners Control Over Their Data Without Sacrificing Governance

27.47

10 Costly Mistakes in Data Integration Projects

35.18

Creating Data Pipelines with Kafka and CloverDX

19.58

Removing Danger From Data

24.14

Moving 'Something Simple' To The Cloud - What It Really Takes

35.11

Publish Data and Transformations over API

16.00

Data Quality - Building Data Pipelines with Bad Data in Mind

31.30

Data Anonymization For Better Software Testing

33.25

Modern Management of Data Pipelines Made Easier

38.10

Turning Data Models into ETL Jobs at the Click of a Button

30:15

Automated Data Architecture Development

15:30

Choosing The Right Data Architecture For Your Business

35:07

Analyzing the Analytics Function

15:35

Mind your D's and Q's: Ensuring Data Quality in Your Projects

29:42

From Ad-Hoc to Automatic

26:36
Processing Large Data Volumes with CloverDX Cluster in the Cloud

One of the key motivations for moving data workloads to cloud is the ease of scaling the infrastructure to accommodate massive data volumes. 

Join us on this webinar to learn about building scalable architectures in cloud using CloverDX Cluster. Learn about:

  • How to use cloud-native components in conjunction with CloverDX to build robust data pipelines 
  • How CloverDX scales to a multi-node cluster 
  • How CloverDX enables infrastructure as code and DataOps
Supporting Data Ops dashboard in CloverDX

DataOps is one of the methodologies that helps fast-moving companies ensure that they can extract value from their business data as soon as possible.

Join us on this webinar to see how CloverDX can help you with your DataOps challenges: 

  • How CloverDX helps during development - ensuring high quality and maintainability
  • How CloverDX helps during testing to deliver high-quality and clean data 
  • How CloverDX helps in production to make sure your data gets delivered where it needs to, on time and with as little hassle as possible 

By adopting DataOps, data teams can react quickly to changing business requirements and deliver the results to their users as soon as they can, while maintaining a high quality of the data. DataOps pushes teams towards more collaboration and heavy automation of their workflows. 

Loading Data Into A Cloud Data Warehouse (Redshift/Snowflake)

Moving a data warehouse to cloud has been the craze for the last few years and more and more organizations are relying on the likes of Redshift and Snowflake as primary landing destinations for their data.

Join our webinar to find out more about:

  • Comparison of on-premise and cloud data warehouse in terms of operations and cost management
  • How CloverDX helps automate data feeds into a cloud data warehouse
  • Combining traditional batch “ETL” with modern data delivery modes in the cloud
From Old School Data Pipelines to DevOps and DataOps

Processing their data effectively is quickly becoming a core competency of more and more companies. Even companies not traditionally associated with “high-tech” must invest into robust IT solutions to be able to effectively extract value of their data. 

DevOps and DataOps have emerged as two common approaches (philosophies even) that help companies manage the complexities of a modern data-centric world. 

Join us and find out more about: 

  • The two approaches and how they can help your organization improve your processes 
  • Basic principles of DevOps and DataOps 
  • Common approaches and tools that can help your organization work more effectively
Formula 3 Group: Staying Small And Agile While Working With Large Enterprise Ecosystems

In this session, we chat with Russ Ronchi and Andrew Spear of omnichannel technology consultancy Formula 3 Group, as they discuss how they keep their company small and agile while working with the likes of Nike, Vans, Ring and True Religion.

Watch now and learn about:

  • How to stay small and agile in the business of connecting large enterprise ecosystems
  • How to approach the build-vs-buy decision
  • How to be efficient and competitive without worrying about building a large team
  • The lessons learned from innovating with a small team in a large organization

Watch it now and learn how smart use of technology can help you achieve scale while staying nimble enough to react quickly.

Why automation is better than Excel data manipulation

How automation considerably reduces cost and effort you're now wasting in Excel.

Many organizations rely upon manual processes that could be automated. We believe it's a missed opportunity; we like to see businesses focus on adding value, not tirelessly laboring over data.

In this webinar we'll explore the difference between the 'manual' approach and 'technological' approach.

Join us and find out more about:

  • How manual data processes silently hurt your productivity
  • What automation means and how it relates to what you currently do in Excel
  • Examples of organizations successfully introducing automation to eliminate errors, speed up business processes to get ahead of competition and to greatly reduce costs
  • When is the right time to consider moving away from manual process
  • Adoption of new technologies without too much friction from your IT department
It's time to ditch your homegrown ETL. It doesn't have to hurt.

It’s only natural to start with a simple solution that you put together using the tools you already have and know well – scripts, databases, or cheap & simple integration services.

In this webinar, we’ll discuss how to tell when it’s time to move on to a more mature platform and the benefits and challenges it brings:

Join us to hear about:

  • Benefits and downsides of home-grown tools VS a modern data management platform
  • When to build in-house and when to look for a ready-made platform
  • What are the often neglected areas that cause headaches over time and how to avoid them
  • How working with a vendor can get you more reliable and quicker results
Building elegant processes for mapping unwieldy complex data structures (JSON, XML, HL7)

Very often complex data structures need to be converted into simpler, homogenized (“flatter”) structures. In this webinar we’ll talk about how to streamline and automate data mapping processes from unstructured formats (JSON, XML, HL7, …) into simpler, manageable structures.

Join us to learn about:

  • Common hurdles in handling complex data structures in JSON, XML, HL7, etc.
  • How to capture mapping information in a collaboration between IT and business users
  • How CloverDX can improve developers’ productivity in manipulating ever-changing data structures
  • How CloverDX’s flexibility allows to cleverly design effective automated pipelines
Surviving a Data Migration
Who should be involved when migrating data between enterprise applications? What does moving data actually involve? How should you navigate the delicate dynamic between IT and business folks?

On this webinar we'll discuss how automation and repeatable processes allows not only faster migration times, but also the added confidence in the migrated data.

Join the webinar and find out more about:
  • Discovering historical "bruises" in your data
  • Importance of repeatability of the migration process (No Excel please!)
  • How to leverage the migration project to improve collaboration between IT & business users (data owners) 
We cover some examples of past projects and the highlight what made them successful.
Bridging Legacy Banking and Agile FinTech with Choice Bank

Jake Tupa, SVP Technology Innovation at one of the fastest growing banks in America, Choice Bank, joins us to talk about data, technology and innovation in the banking and FinTech space.

We'll be discussing the challenges involved in access to and use of data in a traditional banking environment, and how to build an infrastructure that enables innovation.

How does a community bank excel at data innovation?
Join us to hear first hand experiences about:
  • Building data driven services around legacy platforms
  • The interplay between modern FinTech ways of working and traditional banking practices
  • How to build data infrastructure in order to be agile and progressive
  • Modernizing and automating processes and infrastructure
Data Ingest For Faster Data Onboarding

Whether you're trying to onboard new client data or set up new data feeds from all sorts of sources, you need to be fast and efficient.

Watch our webinar where we'll take a look at the challenges and best practises for ingesting data into applications and how to make it easier, faster and quite often just even possible.

Watch now and learn about:

  • Challenges around reading data from foreign sources and how to approach automation of such repeated tasks
  • Data validation challenges and how to set up universal validation scheme
  • How to bring data mapping into the hands of subject matter experts, instead of developers
  • How to effectively write data to its destination
Working with stubborn REST APIs

Ever wondered why some APIs are just so annoying to work with?

Join us for a practical show of how you can deal with complicated APIs in CloverDX.

We'll be looking into:

  • How to connect to REST APIs that require multiple steps, pagination and other complexities
  • How you can easily build custom connectors to API services that do exactly what YOU want without having to code them from scratch
  • How you can add data validation and health checks along the way

 

Running CloverDX In The Cloud (AWS & Azure)

In this webinar we dive deeper into options you have available to run CloverDX in AWS or Azure cloud. 

We look at architecture and best practices when installing CloverDX from packages available in AWS Marketplace and Azure Marketplace. We talk in more detail about: 

  • Which services will be used in each cloud (compute, storage, security and more) 
  • Installation options and proper sizing of the instances 
  • How to connect your Designer to the newly deployed Server and how to deploy a project there.

 

Building APIs and User Interfaces For Your Data Workloads

Watch our demonstration of how you can build custom data APIs (Data Services) and create user-friendly interfaces with a single click of a button.

Connecting applications, either peer to peer or making near real-time data exchanges between applications and data storage, has become a normal part of data workloads. CloverDX is a great platform to support these mixed processes, facilitating exchange of data between storage, applications and people.

Watch now and learn about:

  • Publishing and collecting data over a REST API in CloverDX (Data Services)
  • How to publish simple "Data Apps" for non-technical users to interact with your data jobs
  • What are the common use cases for Data Services and Data Apps and why you should consider using those
  • Advanced use cases and extensions to Data Services and Data Apps
Deploying ETL To The Cloud

The architecture and operation of a data pipeline in cloud is a very different exercise compared to setting up traditional on-prem ETL processes of the past. 

Let’s dive deeper into the architectural patterns (and antipatterns) of cloud when it comes to setting up data processes. We’ll look at the technical considerations and some caveats you might encounter when building in cloud.

This will be a technically oriented session, basic knowledge of cloud products (VMs, Redshift, S3…) will help you fully benefit from the session. 

Watch and learn about:

  • What it takes to set up a production data pipeline starting from zero – the cloud components to use and why (using an example in AWS) 
  • We’ll show and explain an example architecture of a data pipeline in the cloud
  • Estimating costs and how to avoid overruns
Migrating Data Workloads to Cloud

Watch our webinar where we’ll discuss the pros and cons of moving your data to cloud, what to look for and what choices you’ll have to make (and how to make the right ones).

Watch and learn about:

  • Comparison of numerous options for data storage available in AWS, Azure and Google Cloud
  • Ways of moving data between SaaS and on-premise applications and storage
  • Caveats of being locked into a specific ecosystem
  • Ensuring data processes are robust and agile enough to support all the moving parts
  • Dealing with combination of on-premise data (that is not going away) and cloud data
Repeating Data Migrations to Workday

We talk about the important role migration frameworks play for organizations implementing Workday, with a real-life example we did for a client.

Join the webinar and learn:

  • Pitfalls of traditional approaches
  • Benefits gained from repeatability and automation (including some sanity checks)
  • How to scale with modular data frameworks
  • Example of a Workday migration framework/template
Give Data Owners Control Over Their Data Without Sacrificing Governance

Data owners understand their data, and the more hands-on they can be with it, the more strategic advantages an organization has. 

In the webinar we present a unique solution that empowers data owners without the danger of organization losing visibility and governance. (Hint - it enables you to use your data models directly in your data infrastructure).

On this webinar you'll discover how to:

  • Reduce siloed working and potential poor quality data and bad decisions
  • Eliminate the need for data owners, IT and governance teams to use different data tools
10 Costly Mistakes in Data Integration Projects

Data integration projects come in many sizes, shapes and colors. It’s safe to say no two are alike. ​

One thing they do share, however, is their susceptibility to a common set of costly design and implementation mistakes​.

Watch our webinar and learn how to recognize and avoid the common pitfalls!

Whether it be choosing a partner, defining your timeline, or characterizing your data and your intended audience, before you launch your next data integration project.

Creating Data Pipelines with Kafka and CloverDX

Kafka enables you to stream data in large quantities, but doesn't provide any real data-wrangling capabilities. CloverDX can help you work with data in Kafka and create comprehensive and auditable data pipelines. 

Watch the webinar where we'll show you how to create modules in CloverDX that can:

  • Write to or read from topics in Kafka
  • Dynamically enrich incoming data
  • Process Kafka data streams and push to appropriate targets (APIs, data warehouses and so on)
Removing Danger From Data

Watch the webinar for a bird's eye view of the potential dangers data represents to organizations.

GDPR, CCPA, HIPAA and many other regulations and policies force us to take data, its lifecycle and the ways we treat it more seriously than ever before.

In this webinar we'll take a look at the dangers data can present, and show you how you can still get value from your data, without putting your organization at risk.

Moving 'Something Simple' To The Cloud - What It Really Takes

In this webinar we'll discuss what moving 'something simple' to the cloud really involves.

We'll examine the difference between deploying on-premise, the "VM way" and the fully-cloud way. 

And we'll show you a behind-the-scenes look at a real-life case, where a requirement from several business units triggered a hasty implementation at first, then raised some fundamental questions, and eventually lead to a cascade of decisions and an AWS cloud solution.

Publish Data and Transformations over API

In this webinar we'll look at the rise of APIs in modern data pipelines, and show you how you can use CloverDX to integrate applications' data with your ETL processes. 

Join us and learn:

  • The various options for API integrations, and what you should consider when building them
  • How to effectively pass data between systems
  • How CloverDX can help you:
    • Quickly design data processes and publish as REST APIs
    • Collect data from applications
    • Provide data transformations as a service
Data Quality - Building Data Pipelines with Bad Data in Mind

Bad data is so common that it would be seemingly insane to design your data processes and application to count on data being flawless.

Yet, many of us do.

In this webinar we’ll show you some best practices and techniques for assessing and ensuring data quality.

Watch now to learn:

  • Where data quality problems could creep into your processes
  • How (and why) to design with bad data in mind at every step of your process
  • Tips for an effective error handling process
Data Anonymization For Better Software Testing
Watch now and discover how you can generate data that's as lifelike and close to production data as possible, without breaking privacy or compliance regulations.
 
Watch and discover:
 
  • What data anonymization really is
  • How it’s different to generated synthesized data
  • When you should use each version
Modern Management of Data Pipelines Made Easier

From data discovery, classification and cataloging to governance, anonymization and better management of data over its lifetime, register now to learn:

  • How to make data discovery and classification easier and faster at scale with smart algorithms
  • Best practices for standardization of data structures and semantics across organizations
  • What’s driving the paradigm shift from development to declaration of data pipelines
  • How to meet regulatory and audit requirements more easily with better transparency of data processes
Turning Data Models into ETL Jobs at the Click of a Button

Discover how to make your data models directly usable in IT operations.

Bridge the worlds of business and IT by generating actionable code directly from your data models. We'll show you how this approach can:

  • Improve transparency of your data processes - ideal for making compliance simpler
  • Reduce duplication of effort and complex processes involving many teams
  • Accelerate time to production with drastically reduced development cycles
Automated Data Architecture Development

This webinar examines 3 case studies where data integration tools have been just as valuable in developing a data architecture as they are in operating that architecture. 

  • A financial institution that dramatically reduced time to production
  • A company that automated regular updates to an analytics warehouse (and stopped using Excel)
  • An example of anonymizing real data to use in testing, overcoming strict privacy and security issues. 
Choosing The Right Data Architecture For Your Business

How do you choose the right data architecture for your needs?

Watch this webinar and discover:

  • The advantages of replicating operational data into various 'stores'
  • What some of those options involve, including overviews of data warehouses, lakes, hubs, vaults and more
  • Best practices for building those architectures
Analyzing the Analytics Function

This webinar looks at how a data integration platform can enable analysts to spend more time analyzing, and less time on the mundane work such as validating and cleansing data and delivering results.

  • Improve trust in results by protecting analysis from changes in data structure, location or quality
  • Create repeatable analysis workflows easily
  • Automate reading, writing, validation and logging
Mind your D's and Q's: Ensuring Data Quality in Your Projects

This webinar explores some techniques for ensuring data quality in your systems and looks at how you can use CloverDX to improve the quality of your data.

  • See how to detect issues early and prevent them from entering your systems
  • Create actionable reports to allow data quality issues to be understood and resolved
  • See how built-in validation tools in CloverDX can help identify and fix errors
From Ad-Hoc to Automatic

Watch this webinar and see how you can use CloverDX to simplify and automate data integration processes.

We also look at real-life examples of how people use CloverDX for reporting, data migration, data warehousing and analytics.