Business Intelligence is the end-to-end process of turning raw data from your systems into useful insight for people. It covers data collection, ETL, data warehousing, modeling, dashboards and the habits around using those dashboards in daily decisions. In practice, it means your team can answer important questions with confidence, using a shared source of truth instead of scattered spreadsheets.

Simple reporting usually means exporting data from a single system and formatting it in a spreadsheet or a basic chart. Business Intelligence connects multiple systems, standardizes definitions, stores data in a warehouse and provides reusable models and dashboards. BI is designed for repeatable, cross-functional questions, not just one-off summaries.

khajavi.tech covers discovery, data architecture, ETL / ELT design and implementation, data warehouse modeling, metric definitions, dashboard design, data quality checks and ongoing support. We also connect BI with your web applications and product so the analytics layer grows alongside your core systems.

We can work with product and application databases, CRMs, marketing tools, ad platforms, support systems, financial systems, warehouse or logistics tools and more. The key is to decide which systems are sources of truth for each type of data and then design ETL processes that bring them together reliably.

A data warehouse is a structured, long-term store for analytics data. Instead of pulling data separately from each operational system, you load it into the warehouse where entities and metrics are standardized. This makes it much easier to create consistent dashboards, support complex analyses and avoid conflicting definitions across teams.

ETL stands for Extract, Transform, Load. It is the process of pulling data from source systems, cleaning and reshaping it and loading it into your data warehouse or analytics environment. ETL is the plumbing that feeds your BI platform. If ETL is unreliable or unclear, your dashboards and reports will be as well.

In ETL, data is transformed before it is loaded into the warehouse. In ELT, data is loaded first, then transformed inside the warehouse using its processing power. The choice depends on your tools, data volumes and design preferences. We work with both patterns and choose what best fits your context.

Timelines depend on the number of data sources, the state of your current systems and the complexity of your questions. A focused setup with a few sources and key dashboards can be delivered in weeks, while a full multi-team platform can take several months. During discovery, we define a staged roadmap so you see value early instead of waiting for a “big bang” launch.

No. We work with both early-stage startups and established organizations. With startups, the focus is often on building a lean but solid foundation. With larger companies, the work usually involves consolidation, standardization and modernization of existing BI and reporting setups.

Yes. Many teams have a BI tool license but lack a coherent data model or reliable pipelines. We can audit your current setup, refine the data warehouse, redesign metrics and rework dashboards so the tool is finally used to its potential. Often the problem is not the tool itself, but the way data is prepared for it.

We define clear metric definitions, design consistent models and implement data quality checks. These checks cover volumes, valid values, relationships between tables and the timeliness of data. We also set up monitoring and alerts so issues are detected early. Over time, this builds confidence in the BI platform.

We work best with data-driven companies in eCommerce, SaaS and B2B, FinTech, logistics, manufacturing and EdTech. If your teams depend on digital systems and you feel that you are not fully using the data they produce, BI & Data work with khajavi.tech is likely to be valuable.

Your web application is often the main generator of customer and usage data. We connect application databases and events to your data warehouse, define product metrics and build dashboards that show how people actually use your product. Because khajavi.tech also builds web apps, we can design both layers to work well together.

Yes. We have experience optimizing databases, especially SQL-based systems, for both transactional and analytical workloads. This includes index design, query optimization, partitioning strategies and caching where appropriate. The goal is to keep both your application and your BI platform responsive.

In some use cases, daily or hourly updates are enough. In others, near real-time insight is important. We can design architectures that support more frequent updates or streaming patterns where it makes sense, while being honest about the trade-offs in complexity and cost.

We design access control so that people see the data they need and nothing more. This includes role-based access, row-level security where necessary and careful management of credentials. We also consider how sensitive fields are stored and who can access raw versus aggregated data.

That is the goal. We design dashboards and data models so that non-technical users can answer common questions on their own. For more advanced analysis, your data or analytics team can build on top of the same models. We also provide walkthroughs and documentation to help teams become more confident with data.

We start from your requirements, existing stack and internal skills. Then we evaluate which tools fit best in terms of capabilities, cost and maintainability. We avoid introducing new tools when existing ones can do the job, and we focus on stable, well-supported technologies over hype.

KPIs (Key Performance Indicators) are the metrics that matter most for your business. In a BI project, we work with you to define these KPIs precisely, encode them in the data warehouse and use them as anchors for dashboards and reports. Clear KPIs turn raw data into a shared understanding of progress and health.

Yes. A common starting point is to identify the most painful recurring spreadsheets, then recreate them on top of a data warehouse with automated pipelines. This reduces manual work, eliminates copy-paste errors and makes updates automatic instead of a monthly struggle.

Source systems evolve: fields are added, renamed or removed. We design ETL and models with versioning and testing in mind, so changes can be detected early and handled in a controlled way. Communication with your internal teams about planned changes is also part of the process.

Yes. Many clients keep working with khajavi.tech on a retainer or dedicated pod basis. We maintain pipelines, extend models, build new dashboards, onboard new teams and support leadership with new analyses as your business evolves.

We can facilitate conversations with leadership to clarify how data should support your strategy: which decisions need better information, which metrics should be tracked, what level of granularity is appropriate and how BI fits into your long-term roadmap. The output becomes a practical, prioritized data strategy.

When possible, we import historical data to give context to current metrics. This may involve one-time backfills from archives, legacy systems or exported files. We design backfill processes carefully to keep them auditable and repeatable if needed.

That is a common situation. We usually begin with a light discovery phase, identify a small set of high-impact use cases and build a focused initial BI setup around them. Once that is working and delivering value, we can expand the platform step by step instead of trying to solve everything at once.

Yes. We often collaborate with internal data engineers, analysts and product teams. We can help design architectures, implement complex pieces, pair on tricky problems and transfer knowledge so your internal team becomes stronger over time rather than dependent on external help.

We combine regular calls with async updates, shared documentation and clear project boards. You see what has been done, what is in progress and what is next. Trade-offs and decisions are documented so your team has a permanent record, not just chat history.

A typical engagement starts with discovery, moves into architecture and design, then ETL and DWH implementation, followed by dashboarding and enablement. From there, we either hand over a stable platform to your team or continue as an ongoing partner to evolve and maintain it.

We need access to relevant systems or exports, a clear point of contact, and an honest view of your pain points and expectations. The more context you can share about how decisions are made today and where data feels unreliable, the better we can design a BI solution that actually fits your reality.

You can reach out via the contact options on khajavi.tech, WhatsApp or email. Share a short description of your business, current data situation and what you hope BI will help you achieve. We will respond with suggested next steps and, if it makes sense, schedule a focused discovery call to explore the project together.