IDC predicts that global data generation will reach 393.9 zettabytes (ZB) in 2028. As data volumes grow, so do storage costs, and an unorganized environment gives rise to many problems. Ultimately, teams spend their working hours resolving these issues. Meanwhile, management gradually loses confidence in the numbers. How can this problem be prevented? We’ll explain what is included in data warehouse consulting and how this service saves corporate data warehouses from collapse.
Consulting vs. Implementation: What Is Needed and Why
Confusion often arises in the IT services market: people tend to confuse the roles of consulting specialists and engineers who implement BI systems. As a result, some company executives think, “Okay, let’s hire vendors to build the infrastructure we need to work with data.” That’s exactly what happens, but the finished system delivers no business value whatsoever.
Why? To understand the difference between data warehouse consulting and implementation, it is helpful to compare the creation of a system for processing and storing corporate data to the construction of a business center:
An architect analyzes traffic in the area, selects a location for the data warehouse, optimizes the space to meet business objectives, and designs security systems. They understand what needs to be built and why. This is exactly what a consulting specialist does when building a data warehouse.
Site supervisors and construction workers use the architect’s drawings to work with pipes, cables, concrete, bricks, and wood. Their job is to ensure high-quality technical execution. Data warehouse development engineers play a similar role.
When hiring a consultant, organizations should expect them to develop a strategic plan, not to write code. The specialist must understand what specific business metrics mean for each division of the company and bring them into alignment. They must ensure the secure use of data in compliance with security standards. Implementation, meanwhile, is the final tool through which the consultant’s strategy is carried out.
What Does Data Warehouse Consulting Entail?
Let’s take a look at what a data warehouse consultant does day to day. The standard process involves at least four stages.
1. In-depth audit
The first step is typically an assessment of the current infrastructure. In particular, consultants look for data silos—isolated databases that do not share data with one another. They also assess the company’s technical debt and create a roadmap for transitioning to clean analytics without disrupting business processes.
2. Choosing a technology stack
There are quite a few technology platform developers on the market. Each claims that their product is the best. The consultant’s role is to act as an independent party who calculates the total cost of ownership and return on investment, and selects the architecture (cloud, on-premises, or hybrid) that best fits the client’s specific business objectives. A focus on business needs, rather than trends or personal connections with developers, is what distinguishes a good consultant from an ordinary one.
3. Architectural Modeling
At this stage, consultants are developing complex multidimensional models that will ensure the fastest possible processing of analytical data, regardless of the number of rows. They also design data migration paths and choose between two options: classic ETL or modern ELT (ETL involves transforming data before loading it into the data warehouse, whereas ELT first loads raw data into the data warehouse and then processes and transforms it).
4. Data Governance and Security
The system will be useless if there’s no trust in it. That’s why consultants create sets of rules: these cover access controls, data protection against leaks, anonymization in accordance with the GDPR, individual accountability for each dataset, and so on.
When Should a Company Hire a Data Warehouse Consultant: 5 symptoms
Here are 5 factors that indicate the time for trying to manage data flows on your own is over:
- A complete crisis of trust. Key metrics differ across departmental reports. As a result, representatives from each department argue with one another, convinced that their figures are the most accurate. Against this backdrop, managers stop trusting any data at all.
- Outdated analytics. The company’s specialists spend most of their time manually transferring data from various systems into summary tables. As a result, by the time a report is prepared, the figures are already 1–2 weeks out of date, and the business misses important market opportunities.
- The infrastructure can’t keep up. The business is scaling, and the existing databases can’t handle the load. Dashboards freeze, and the morning data export ties up all of the company’s available resources.
- The company is unable to handle everything on its own. Due to the sky-high salaries of data engineers and a shortage of specialists in the market, the company cannot find a qualified professional. Furthermore, the existing IT department lacks experience working with Big Data.
- The system has been implemented, but there are no results. The company purchased a license and had some nice dashboards designed, but the system runs slowly or the data is still inconsistent. It is impossible to make management decisions based on this data.
A Day in the Life of a Consultant
To better understand why data experts are so valuable to an organization, it’s worth taking a look behind the scenes of the profession. Specialists from Cobit Solutions have shared their insights here. According to them, data warehouse consulting is about finding the right balance between a company’s needs, user convenience, and system capabilities.
A typical morning for a consultant starts with communication. The consultant conducts a series of interviews with non-technical stakeholders—for example, asking the CFO how they envision the margins. This “business pain” is then translated into technical specifications.
After that, the consultant gets down to the engineering work. They dive into writing complex SQL procedures, configuring orchestration tools, and modeling cloud databases. They design pipelines that collect “raw” data from CRM and ERP systems, clean it of errors, and neatly organize it on the virtual shelves of the new data warehouse.
The consultant may also set aside time during the day for a workshop with the organization’s internal team. They share some of his expertise with them so that, once the project is implemented, the company will be able to maintain the system on its own.
Why are Small and Medium-sized Businesses in the Mix Too?
There is a widespread myth in the business world that data warehouse consulting is a service exclusively for multinational corporations, industry giants, and market leaders. That used to be the case—about fifteen years ago, when organizations purchased their own servers and maintained bloated IT departments.
The rules have changed with the introduction of cloud technologies. Pay-as-you-go pricing models (where you pay only for the resources you use) have made enterprise analytics accessible to small and medium-sized businesses.
That’s why even a small company can afford a data warehouse. What’s more, the benefits of implementing one can be realized faster than in a large organization. Here’s why:
- Not only developers, but also marketers and sales managers have access to powerful analytics. Anyone can generate a report in just a few clicks (Self-Service BI).
- Instead of simply copying numbers from a spreadsheet, employees with access to the system begin to look for insights and generate ideas.
- With a reliable archive of historical data, a business can forecast demand and adapt to the market faster than its sluggish giant competitors.
So if you feel like your company is drowning in data but lacking in insights—maybe it’s time to stop relying on traditional spreadsheets and turn to the architects of the digital future of business.
FAQ
What exactly does a data warehouse consultant do?
They are a hybrid of a strategist and an IT engineer. The consultant analyzes your infrastructure, solves the problem of “data chaos,” designs a unified data warehouse architecture, creates automated data collection pipelines (ETL/ELT), and ensures that your data is clean, secure, and ready for immediate analysis. They help companies transition from intuition-based decision making to a data-driven culture.
How do I know if my business needs data warehouse consulting?
If your departments can’t agree on basic metrics (such as monthly revenue), if reports are compiled manually over the course of weeks, if your systems can’t handle the growing volume of data, or if you simply don’t have the in-house expertise to build a cloud-based analytics architecture—these are clear signs that you need to bring in outside expertise.
How long does a typical data warehouse consulting engagement last?
The general industry standard for building a fully functional data warehouse from scratch is 6 to 9 months. However, the timeline depends heavily on the size of the company. Small businesses can deploy a basic solution in just 2–3 months. Mid-sized businesses require 4 to 8 months to build complex logic and integrate multiple systems. The enterprise segment requires 9 to 18 months to process tens of terabytes of data and implement machine learning systems.
Can a small business benefit from data warehouse consulting?
Absolutely. Thanks to modern cloud solutions that don’t require the purchase of physical servers, small businesses can access enterprise-level analytics at an affordable price. This allows small companies to automate routine tasks, democratize access to information, and respond instantly to market trends, gaining an unprecedented competitive advantage.
