NORMLZ

NORMLZ

HubProsper
dbt

dbt

dbt Labs
5.0 out of 5 stars
NORMLZ dbt

Related Products

  • Plauti
    4.4 out of 5 stars 124 Ratings
    Visit Website for Plauti
  • Okyline
    5.0 out of 5 stars 2 Ratings
    Visit Website for Okyline
  • D&B Connect
    4.1 out of 5 stars 189 Ratings
    Visit Website for D&B Connect
  • SCIKIQ
    4.6 out of 5 stars 14 Ratings
    Visit Website for SCIKIQ
  • DataBuck
    4.8 out of 5 stars 6 Ratings
    Visit Website for DataBuck
  • DataHub
    4.5 out of 5 stars 10 Ratings
    Visit Website for DataHub
  • Semarchy Data Platform (SDP)
    4.7 out of 5 stars 64 Ratings
    Visit Website for Semarchy Data Platform (SDP)
  • Code-Cube.io
    4.6 out of 5 stars 8 Ratings
    Visit Website for Code-Cube.io
  • HubSpot AEO
    4.4 out of 5 stars 151 Ratings
    Visit Website for HubSpot AEO
  • InboxAlly
    4.7 out of 5 stars 136 Ratings
    Visit Website for InboxAlly
NORMLZ:

About

NORMLZ is a data normalization tool that standardizes and cleans inconsistent information in HubSpot. The software addresses the challenge of managing large datasets where variations in data formats hinder analysis, campaigning (lost revenues), and reporting. The platform directly integrates with your HubSpot account, with Salesforce and Apollo support roadmapped. The engine identifies and standardizes variations, such as unifying "CEO," "C.E.O," and "Chief Executive Officer" into a single format. Location data like "New York," "NYC," and "New York City" is consolidated, and company names such as "IBM Corp" and "IBM Corporation" are normalized.
dbt:

About

dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.
NORMLZ:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
dbt:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
NORMLZ:

Audience

HubSpot users
dbt:

Audience

SQL users looking for a ETL solution to engineer data transformations
NORMLZ:

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported
dbt:

Support

Phone Support Not Supported
24/7 Live Support Supported
Online Supported
NORMLZ:

API

Offers API Not Supported
dbt:

API

Offers API Not Supported
NORMLZ:

Screenshots and Videos

No images available
dbt:

Screenshots and Videos

NORMLZ:

Pricing

$5/month
Free Version Not Supported
Free Trial Supported
dbt:

Pricing

$100 per user/ month
Free Version Supported
Free Trial Supported
NORMLZ:

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software
dbt:

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 4.8 / 5
design 4.8 / 5
support 4.2 / 5
dbt:

Pros & Cons from Real Users

Pros

  • Ease of use and Features. Easy to setup, integrate, and get started quickly Less maintenance Out of the box CI/CD integration with Git Easy to learn.
  • - Credential and version management is offloaded to the cloud - Simple-to-use orchestration - Seamless state management - Integrated documentation and lineage - Collaborative development experience - Native CI/CD integration - Centralized logging and observability - Enterprise-grade access control and auditability - Easy environment management - Rapid onboarding for new users
  • We use dbt for our data transformations. It's been a game changer from a Data Engineering and Analytics Engineering standpoint. It has accelerated our migration from legacy systems and made our pipelines 80% faster. We have increased visibility in our projects, a catalog and many other data quality indicators.
  • dbt has been one of the most transformative tools in my data career. It gives teams a clean, maintainable way to translate business logic into reliable, production-grade data models. It standardizes the entire development lifecycle — modeling, testing, documentation, version control, CI/CD, and lineage — in a way that allows analytics engineers and data engineers to work with clarity and confidence. It’s the backbone of our governed analytics strategy. Exceptional developer workflow: Modular SQL, version control, built-in testing, documentation, and macros allow us to scale complex business logic with consistency and reliability. Scales with organizational change: dbt has allowed us to redesign core product and customer analytics with patterns that are resilient to future product launches and schema changes.

Cons

  • Limited product Usage metrics. Product usage insights/Metrics can be better. Metrics around AI usage by developers with in the product will help.
  • - Individual capabilities are not as robust as dedicated tools. for example, orchestration is simple to use but lacks the flexibility, customization, and advanced scheduling logic of dedicated orchestrators
  • I think that the pricing model can easily become a barrier. The cost per model run is a terrible bottleneck for us and affects our capacity to architect following best practices.
  • dbt IDE could be more flexible with Git operations. Advanced users would benefit from features like git stash, more granular branch management, and better conflict-resolution tools directly in the IDE. This would remove friction during rapid iteration or when working across multiple branches. More built-in patterns for complex incremental modeling would be helpful for teams dealing with very high data volumes and dynamic product schemas.
NORMLZ:

Training

Documentation Not Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported
dbt:

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Supported
NORMLZ:

Company Information

HubProsper
Founded: 2025
normlz.com
dbt:

Company Information

dbt Labs
Founded: 2016
United States
www.getdbt.com
NORMLZ:

Alternatives

dbt:

Alternatives

DataHub

DataHub

4.5 out of 5 stars
NORMLZ:
dbt:
TIMi

TIMi

4.9 out of 5 stars
NORMLZ:
Adverity

Adverity

Adverity GmbH
dbt:
Dataiku

Dataiku

5.0 out of 5 stars
NORMLZ:
DataMatch

DataMatch

Data Ladder
dbt:
NORMLZ:
RingsTrue

RingsTrue

Cloud Ursa
dbt:
SCIKIQ

SCIKIQ

4.6 out of 5 stars
NORMLZ:

Categories

Data Quality Supported
dbt:

Categories

Big Data Supported
Data Catalog Supported
Data Engineering Supported
Data Integration Supported
Data Lineage Supported
Data Modeling Supported
Data Pipeline Supported
Data Preparation Supported
Data Quality Supported
DataOps Supported
ETL Supported
Semantic Layer Supported
dbt:

Big Data Features

Collaboration Supported
Data Blends Not Supported
Data Cleansing Supported
Data Mining Not Supported
Data Visualization Not Supported
Data Warehousing Not Supported
High Volume Processing Not Supported
No-Code Sandbox Not Supported
Predictive Analytics Not Supported
Templates Not Supported

Data Lineage Features

Database Change Impact Analysis Supported
Filter Lineage Links Supported
Implicit Connection Discovery Not Supported
Lineage Object Filtering Not Supported
Object Lineage Tracing Not Supported
Point-in-Time Visibility Not Supported
User/Client/Target Connection Visibility Not Supported
Visual & Text Lineage View Not Supported

Data Preparation Features

Collaboration Tools Supported
Data Access Not Supported
Data Blending Supported
Data Cleansing Supported
Data Governance Not Supported
Data Mashup Not Supported
Data Modeling Not Supported
Data Transformation Not Supported
Machine Learning Not Supported
Visual User Interface Not Supported

ETL Features

Data Analysis Not Supported
Data Filtering Supported
Data Quality Control Supported
Job Scheduling Not Supported
Match & Merge Not Supported
Metadata Management Not Supported
Non-Relational Transformations Not Supported
Version Control Not Supported
NORMLZ:

Integrations

AccessOwl Not Supported
Azure Marketplace Not Supported
Collate Not Supported
DQOps Not Supported
GetDot.ai Not Supported
Grok Bot Not Supported
Grouparoo Not Supported
Lightdash Not Supported
Meltano Not Supported
OpenMetadata Not Supported
Pantomath Not Supported
Paradime Not Supported
Select Star Not Supported
Sifflet Not Supported
Snowflake CoCo Not Supported
Spresso Not Supported
Stonebranch Not Supported
TROCCO Not Supported
Zenlytic Not Supported
nao Not Supported
dbt:

Integrations

AccessOwl Supported
Azure Marketplace Supported
Collate Supported
DQOps Supported
GetDot.ai Supported
Grok Bot Supported
Grouparoo Supported
Lightdash Supported
Meltano Supported
OpenMetadata Supported
Pantomath Supported
Paradime Supported
Select Star Supported
Sifflet Supported
Snowflake CoCo Supported
Spresso Supported
Stonebranch Supported
TROCCO Supported
Zenlytic Supported
nao Supported
NORMLZ:
Claim NORMLZ and update features and information
Claim NORMLZ and update features and information
dbt:
Claim dbt and update features and information
Claim dbt and update features and information