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Introduction
Imagine the scene: it's Monday, 9am. The sales team needs a pipeline , the financial one wants to design cash flow, marketing wants to cross leads with conversion. All at the same time. And the IT team, of course, becomes the company's “database”.
If you identify yourself, you are not alone. 95% of organizations are still unable to organize and deliver data in a practical way for each area , as shown in the Gartner .
In the end, what is missing are not given, but a structure that uncomplicates access, divide the information by area and delivers speed , without losing control. That's where Data Mart makes all the difference. It is like an intelligent data extension of Data Warehouse : leaner, specific, designed to deliver to each area what it needs - without overloading the IT team.
In this article, we will explain why Data Mart is the right shortcut for teams that need to act fast, how it works in practice and what to consider to take the next step. Because, in the end, since it is delayed given that it does not serve.
Enjoy the read!
What is a date Mart and what does it fit?
For many companies, the difficulty is not in data, but in turning this data into clear answers to each area of the business.
That's where Data Mart . The term "Mart" comes from English Market , that is, a segmented "data market", where each team finds only what they really need to consume. In practice, it is a way to “slice” excess information and deliver ready -made blocks for use , without mess or waste.
In essence, Data Mart acts as an expert extension of Data Warehouse . While Warehouse concentrates everything in one place, Data Mart organizes smaller and specific blocks, ready to be used by sales, marketing, financial, all without queues, without rework, without overloading you. We can also make the analogy to the structure known as the “medallion” of bronze, silver (Silver) and Gold (Gold), where Data Mart is “gold”.
Thus, each area gains more autonomy to generate reports, consult indicators and make decisions more safely, without having to dispute space with other strategic demands of the company.
But there is not just a way to create a date Mart . Next, let's understand what are the main types and when it makes sense to use each one.
Data Marts Types
Overall, data Marts can be structured in three main ways, depending on the level of integration with the remaining data architecture :
- Date Mart Dependent : It is built from the corporate Data Warehouse All data come from a single central source, ensuring consistency, governance and standardization;
- DATA MART INDEPENDENT : Appears from specific operational sources, without necessarily passing through Data Warehouse . It is faster to implement, but requires extra attention with quality and integration;
- Hybrid : Mix the two formats. It combines data extracted from Warehouse with information from external systems when necessary. It is an interesting option for companies that already have a robust central base, but need flexibility.
Each format solves a type of need , and understanding this difference is important to define how the date Mart can generate value in a practical way.
With that in mind, the question now is: How does Data Mart really put order in the mess ? This is what comes next.
How a Data Mart organizes the data
Having all the data stored in one place does not solve much if, in practice, the team is still stuck in time consuming, incomplete reports and bottlenecks in IT . This is where Data Mart enters the scene: it is not just a “mini database”, but a structure that cuts, filters and delivers only what each area really needs .
Data Mart refers to three fundamental pillars that define how it organizes the information clearly and lightly:
- Specialization by Business Area : The first pillar is the division by theme or area. Sales, for example, do not want to browse account data to pay; Want pipelines , goals and conversion ready for consultation. Already the financial needs projections, costs, real flow. And marketing wants to cross leads , funnels and campaign results simply, without depending on endless spreadsheets. This separation ensures that each team works focused, without wasting time scouring everything;
- Speed in data query : With the information already organized, consultations run more lightly. The data comes fast, without overloading the IT team with repeated operational orders. It's like having several short paths instead of a single congested road every time a new question arises;
- Optimized performance : The last pillar is the technical balance. Data Mart works with lower information blocks, which relieves the volume processed in the data warehouse . Thus heavy reports do not lock it all, even at peak times. For the technical team, this means less bottleneck and more infrastructure fluidity.
With this well -structured base, Data Mart gets out of paper as “just another technical tool”, and becomes a real part of everyday life. After all, organizing is just the beginning: the value appears even when all this connects with those who decide - and that's what we explore next.
Main practical advantages of using a date Mart
A data Mart does not stop organizing tables: it is what makes the information out of the drawer and get to those who decide with confidence.
In many companies, the routine is still marked by contradictory reports, dashboards and spreadsheet versions that no one knows what the final is. No wonder, 70% of professionals say they lose up to one day a week waiting for data , according to Forrester . A date Mart shortens this way, but the gain goes beyond.
According to McKinsey , companies that segment data by area have up to 42% more chance to generate actionable insights , because separation makes information reliable in origin, without rework every time a number changes.
With this, there are advantages that go beyond the technician:
- Bi Vivo that follows the business : Dashboards are no longer static and roll in real time, fed by clean data, without manual rework. This shortens the way between those who collect the data and who needs to present the result;
- Governance that works without locking : Data Mart defines who accesses what, avoids duplicity of information and gives traceability. Thus, each area understands its limits, the IT team focuses on what matters and the risk of noise falls;
- Solid base for AI and advanced analysis : Segmenting data in an organized way is not just a performance gain, but it feeds predictive models without differences. With reliable blocks, the company tests, adjusts and scale Artificial Intelligence (AI) sustainably;
- Less cost scalability : According to Boston Consulting Group (BCG) , a segmented architecture can reduce processing costs by up to 30% , releasing budget for what really makes a difference - improving products, innovating, climbing data projects;
- Real autonomy, not speech : each area can answer questions without queue, create reports, test hypotheses and adjust whatever is needed with the most agility. Thus, the data is no longer a bottleneck and becomes input to evolve the business.
When each part fits, Data Mart makes the circular data lightly and confidence in the pace of those who need to decide fast.
And it is precisely so that it works that every detail counts, from capture to the choice of tools. Let's understand where to start this implementation?
Step by Step to build a date Mart
Having an data Mart is not pushing a button, but you don't have to become an endless project either. The secret is to respect some essential steps , in the right order, to avoid rework and ensure that the structure operates from the beginning.
Here is what can not be missed:
- Map your data sources : Everything starts by knowing where the information comes from: ERP, CRM, financial systems, spreadsheets or external APIs? What is critical? Who is the owner? How often is each base updated? To skip this step is to make room for duplicate information, outdated data and rework when creating reports;
- Organize thematic blocks and define governance : with clear sources, it's time to structure how data will be grouped. Which blocks do each area serve? What is specific sales, marketing , financial? Here comes governance: Who accesses, edits or validates each set?
This division prevents Data Mart from becoming a messy spreadsheet and ensures that each team has what they need without overloading IT;
- Configure the ETL/ELT flow : time to move all this. Extract , Transform , Load ) or ELT ( Extract , Load , Transform processes come in here , which basically extract data from various sources, transform or standardize everything and carry on data Mart , ready for use.
Tools such as Fivetran , Airbyte or Data Build Tool ) automate this step with low code and version control, releasing the team of repetitive manual tasks;
- Valide, test, and adjust continuously : No data Mart is born ready forever. It is essential to create periodic validation processes: review if data arrive clean, if the blocks still answer the real questions of the areas and if new sources need to be integrated. This continuous adjustment avoids hidden bottlenecks and keeps everything relevant as the business evolves.
Following each step, Data Mart does what it needs: organizes blocks, guarantees governance, automates flow and keeps everything aligned with the areas. And for this real structure, it is the choice of the platform and the BI tools that closes the cycle . This is what we will detail now, keep following!
Platforms and BI: Where Data Mart comes to life
When everything is built and organized, the time comes to put this data to really run . And that's where two fundamental layers come in:
- cloud infrastructure , which guarantees storage, processing and scalability;
- And Business Intelligence ( Bi ) tools, which turn it all into dashboards , clear reports and views, ready for those who decide.
It is robust base combination takes the data Mart of the backoffice and puts living information on the table of those who need to have the right one at the right time.
Then we approach a little more about them.
Cloud platforms ( snowflake , bigQuery , Redshift , Synapse )
Today, hardly a date Marthe is supported outside the cloud . After all, it is like a “fertile ground” where data Mart grows without physical limit. This is where the data blocks are stored, processed and ready to run heavy queries, even when demand fires.
Platforms like Snowflake , Google BigQuery , Amazon Reshift or Azure Synapse Analytics are the most chosen today because they help the business climb without investing in internal servers . With them, companies pay for actual use, adjust processing according to demand and integrate everything with pipelines , simply.
Each one has its asset:
- Snowflake : It is flexible to separate processing and storage, useful for those dealing with consultation peaks;
- BigQuery : Works on demand; Good to avoid waste when use is variable;
- Redshift and Synapse : Made the lives of those who already run services at AWS and/or Microsoft .
More important than the brand, it is knowing which platform makes sense for the volume of data, the flow of consultations and the level of security that the business needs today, and in the future .
BI Tools ( Power BI , Tableau , Looker , Metabase )
If the cloud is the terrain, BI is the showcase: this is where the structured data becomes insight , report and practical response in the hand of those who decide.
Next, we list the most used tools, which translate data blocks into dashboards and easy to explore analyzes:
- Power BI : known for native integration with the Microsoft and ready -to -use interactive reports;
- Tableau : Strong in advanced views and rich panels to explore data crosses;
- Loaking for BI : Highlight for integrated analysis in cloud data environments, with centralized governance;
- Metabase : Open Source to create dashboards , with lower input cost.
More than just showing beautiful numbers, a BI well connected to Data Mart ensures reliable access and autonomy for each area to look at what matters, while the IT team takes care of governance, performance and evolution of architecture.
With the right infrastructure, Data Mart supplies BI, and the data becomes a practical response, without stopping who decides. This is how each part adds , from storage to analysis, and prepares the business to grow based on clear information. And to orchestrate all this with safety, integration and scale, Skyone enters as a definitive partner in the process, from end to end.
Skyone: Governance, Integration and Scalability for your Data Marts
Having an data Mart to BI is what ensures that each area has clear answers at the right time. But those who live this in practice know that the challenge does not stop in structuring : it remains every day, with growing data, changes that change and new sources that emerge.
At Skyone , we help companies build, maintain and evolve this flow without creating premises or plastered processes . In everyday life, this means automating extraction, turning data from different origins, organizing everything into the cloud with real scalability, and maintaining governance alive, even when the volume fires.
No matter which cloud platform the team uses, or which BI tool. What makes a difference to us is to ensure that everything "talks" the right way , without stopping those who need an answer. Because from this, the IT team can focus on what really moves the strategy : evolving processes, maintaining security and supporting areas with data ready to become action. At Skyone the infrastructure for metabase is already ready and delivered.
If you want to understand how to get bottlenecks out of the way and make your operation lighter, seek us! Talk to a skyone expert and see, without commitment, how it runs in practice, in your scenario, your way!
Conclusion
When each area has access to the right data, the answers come to the pace that the business requires - more accurately, less waste of time and more security to act . This is what a data Mart offers: a clear structure, easy to evolve and that keeps the information useful from end to end.
Everything we explore here shows that organizing data is not just a technical step : it is a practical basis for giving team autonomy, supporting strategic decisions, and making room for advanced analysis, AI and truth innovation .
If this content was useful for you, keep finding more ways to unlock the potential of your data! Explore our Skyone Blog and find other texts on cloud, integration, architecture and trends.
FAQ: Frequently asked questions about data Marts
Before creating or using a data Mart, it is normal to have doubts about what it is indeed, how to differ from other data structures and if it is worth investing in this approach.
Next, we gathered direct answers to the most common questions to help you better understand if this solution makes sense in your context.
Data Mart is equal to date warehouse ?
No. Data Warehouse is the central repository where the company stores large data from different sources, in a consolidated manner. Data Mart is like a specialized “clipping” of this whole: an organized data subset to meet a specific area or theme (eg sales, marketing or financial).
In practice, Data Warehouse keeps everything, and Data Mart separates, filters and delivers what each team really needs, without having to consult all the gross volume.
Who should use a date Mart ?
Companies of all sizes can use data marts . However, it makes even more sense in organizations where different areas need to access specific data quickly, always depending on IT to generate reports.
If the company has a considerable volume of data and wants to give more autonomy for sales, marketing, financial or operations to work with clear cutouts, Data Mart is a practical structure to accelerate consultations, reduce overload on the data warehouse , and better organize governance.
Is it safe to store sensitive data on a date Mart ?
Yes, as long as architecture follows good security and data governance practices. A date Mart can store sensitive information (such as financial data or sales metrics) as long as there are well -defined access layers, encryption, authentication controls and constant update of those who can view each block.
In most cases, Data Mart is part of a larger architecture (with Data Warehouse compliance policies . This ensures that the right data reaches the right area, with no risk of leakage or misuse.
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