Megaladata

Healthcare organizations process massive amounts of patient data every day. Automated data workflows help keep it clean, reliable, and ready for better decisions. 🦈

Businesses are investing heavily in data, but real value comes only when analytics becomes a reliable decision-making tool.

AI is not a universal solution: It delivers results in specific, high-volume, repeatable processes like text processing, customer communication, documentation, code generation and recommendations. Success depends less on “using AI everywhere” and more on integrating it into stable workflows, with strong data quality and clear business goals.

At the core, data quality still defines the value of every AI-driven insight.

5 Practical Ways to Use AI in Data Management Here are five areas where AI delivers measurable results: 1. Text processing Text data is one of the most labor-intensive areas of analytics, particularly in large organizations, due to its unstructured nature and the high volume of manual work required.

MCP in Megaladata 🦈 brings together low-code and AI to rethink how data becomes context for intelligent systems.

Instead of treating AI as an add-on, Megaladata makes it a native part of the workflow, where structured, real-time, and well-governed data is always available through MCP (Model Context Protocol).

The result: faster setup, better context, and full control over what AI can see and use.

🔹 SIMPLE: Low-code
🔹 FAST: Real-time data
🔹 COMPATIBLE: MCP

MCP will be available in the next Megaladata update as part of the Enterprise version.

Megaladata 7.3.2 addresses memory leaks and fixes bugs in the Import group components, Calculator, Calculator (Tree), certain сonnections, and the Cluster Profiles visualizer.

Megaladata 7.3.2 - Release Notes Bug fixes BatchLauncher Issue: When calling BatchLauncher without parameters, the help information displayed did not include the - symbol before variable names on Linux, potentially confusing users. Fix: Added the missing - symbol ( #12015).

AI doesn't make mistakes. It's just given the wrong data. Even the most powerful models are useless without quality, properly prepared context. Megaladata's MCP server transforms AI from a generic answer generator into a controlled business analytics tool.

MCP Server in Megaladata: From AI's "Smart" Answers to Real Business Solutions The core issue: data, not models When it comes to practical AI applications, the key question isn't about model specs or hardware, it's about what data the large language model (LLM) receives.

April 1st rule: Never trust an Excel screenshot. 🦈

Just like missing cargo in transit can turn into a headline, unseen risks in financial operations can turn into real business impact.

🦈 Megaladata helps finance teams identify suspicious transactions, assess risk, and optimize financial operations using advanced analytics and predictive modeling.

From audits to forecasting, turn financial data into action, and prevent issues before they escalate.

🦈 Smarter Retail with Megaladata

Retailers and CPG companies deal with huge amounts of data every day – thousands of products, multi-channel sales, customer info, and supply chains. Traditional tools can’t keep up: slow processing, manual work, and messy data waste time and money.

Megaladata makes it simple:
1. Watch KPIs in real time: See trends and issues as they happen
2. Plan inventory smarter: Avoid overstock and stockouts with predictive analytics
3. Price and promote effectively: Make better decisions to boost revenue
4. Keep supply chains running smoothly: Coordinate suppliers and automate repetitive tasks

In action: Big multi-format retailers juggle tens of thousands of products across stores and e-commerce. With Megaladata, they adjust quickly to demand, automate decisions, and keep customers happy – all without heavy IT work.

“Remove duplicates.”
“Fix the outliers.”
“Clean the dataset.”

Sounds easy, right? 😅 But what do these terms actually mean?

Outliers are those strange numbers that look suspicious. Sometimes there are errors. Sometimes they are the most interesting part of your data.

Duplicates are repeated entries. If you do not remove them properly, your sales might look higher than they really are. Great for your ego. Not great for making decisions.

Missing values are empty cells. Ignoring them can skew your results badly.

Data cleaning is basically making sure your data makes sense before you trust it.
For if your data is messy, your conclusions will be messy too.

🦈 Behind every good analysis, there is some essential cleaning. Megaladata does it for you!

🇦🇲 Armenian Startup Megaladata Expands Globally From Yerevan to Help Businesses Process Data Faster & Make Smarter Decisions
➖➖➖
As companies generate more data than ever before, many still struggle with familiar bottlenecks: manual reporting, scattered data sources, slow workflows, and delayed decisions. From Yerevan, Armenian analytics platform Megaladata is building a solution to that global problem, helping organizations process massive volumes of data, automate analytical workflows, and make faster, smarter decisions..

At the center of that effort is Managing Director Samvel Arustamov, a specialist in data analytics, AI, machine learning, ETL, and data engineering, helping lead the company’s international growth while contributing to Armenia’s rising role in the global tech ecosystem.

Megaladata is the fastest low-code platform for advanced analytics and ETL. Its purpose goes far beyond data analysis. The platform is designed to eliminate the gap between the moment data appears and the moment decisions are made.

About The Team
Development began in 2012 to address a specific challenge: the bottlenecks caused by manual data analysis. With a clear mission: to make advanced data analysis accessible to everyone.

Today, Samvel Arustamov leads a fast-growing international team headquartered in Yerevan.

A specialist in data analytics and modern analytical technologies, Arustamov has been working in the field of data analytics since 2020 and has been involved in the development of the platform since then. His professional focus includes AI, machine learning, ETL, and data engineering.

As a member of the Armenian Diaspora, he actively contributes to the development of Armenia’s tech ecosystem. Under his leadership, an international partner network has been established with participants from more than 10 countries.

A Global Challenge, Solved in Armenia
Today, almost every company calls itself data-driven. However, many businesses still didn’t overcome the same old problems
* Manual reports
* Scattered data sources
* Excel files sent back and forth between departments
* Analysts waiting for data from IT
* IT waiting for properly defined requirements.

As a result, decisions are made not when the business needs them, but only when it finally becomes possible.

This is the paradox of the modern economy: data has become the most abundant resource, yet access to clean, high-quality data remains limited. As data volumes grow exponentially, accelerated by automation and GenAI, the main bottleneck is no longer a lack of ideas or specialists, but the performance of analytics systems.

This is exactly the problem Megaladata was created to solve.

In today’s environment, making fast, data-driven decisions is critical. If an analysis workflow takes hours, it loses practical value. If pipelines are slow or unstable, trust in data quickly disappears.

That is why performance in Megaladata is not a standalone feature. It is the foundation of the entire architecture. The platform enables companies to process massive volumes of data, build complex analytics workflows, and automate processes without programming or lengthy infrastructure adjustments.

An Armenian Tech Success Story
Headquartered in Yerevan, Megaladata reflects the strength of Armenia’s technology sector. The company has built a global footprint while maintaining strong roots in the Armenian innovation ecosystem, contributing to the country’s growing reputation as a rising center for data science and digital transformation, a trajectory reflected more broadly by major developments such as the recent Nvidia and Firebird investment initiative in Armenia.

Driven by local talent and international vision, Megaladata shows how Armenia can compete on the world stage in high tech and analytics. The company is already present with clients and partners in Europe, Latin America, the Middle East, and Southeast Asia, and is preparing for the next phase of growth by entering the North American market, seeking long-term collaborations with partners and enterprises that share its data-driven approach.

A Startup with a Mature Product
Despite its recent launch on the international stage, Megaladata has already proved to be valuable in several markets.

The platform supports daily analytics workflows, ETL pipelines, automated calculations, and recurring models. Companies rely on Megaladata as an operational tool, not as an experiment or proof of concept. It is a mature technology already used in real production environments.

Today, international expansion is the company’s top priority. Megaladata is not built for a single market. It is an infrastructure for modern analytics: scalable, high-performance, and production-ready.

Megaladata’s Approach to the AI Revolution
AI has become the loudest voice in modern business IT. While its impact on how organizations operate is undeniable, integrating AI into critical decision-making remains a complex and unresolved challenge.

Megaladata has taken a pragmatic and disciplined approach to AI, applying it only where its benefits are clear and measurable. Across the rest of the platform, Megaladata relies on a robust low-code architecture that ensures transparency, control, and high performance.

This balanced strategy allows organizations to leverage advanced AI capabilities without sacrificing trust or operational stability, delivering the best of both worlds: the power of artificial intelligence combined with the reliability of low-code analytics.

What Megaladata Delivers to Businesses
In a single platform, Megaladata brings together:
* data processing and integration
* advanced analytics and modeling
* automation of analytical workflows

Companies use it to clean and standardize datasets, integrate information from ERP, CRM, databases, files, and APIs, build forecasts, scoring models and risk predictions, and automate daily calculations and reporting.

In essence, Megaladata turns analytics into a continuous, seamless process.

Empowering the Community
Megaladata’s mission is to make advanced and professional analytics mainstream and accessible.

The low-code approach lowers the entry barrier significantly: an advanced Excel user can learn the platform and start working with real data in about two weeks. This puts analytics into the hands of domain experts, not only IT specialists.

In addition, the company offers a free desktop version: Megaladata Community Edition. It is built for personal and educational use and comes with no limitations on time, data volume, or available algorithms. Community Edition allows companies and professionals to start working with analytics without financial barriers and gradually build internal expertise.

Megaladata makes analytics accessible not by simplifying capabilities, but by combining extreme performance, a low-code approach, and open access to technology.

Looking Ahead
With data now at the core of competitive advantage, Megaladata is steadily expanding its platform capabilities and strengthening its global footprint. The company remains committed to empowering more businesses to transform data into clear, actionable insights.

From Armenia to global markets, Megaladata is not just solving data problems, it is shaping a future where analytics is inclusive, strategic, and accessible to every organization.

Keep dodging your pending Excel problems… or step into a platform built for 50+ GB datasets, millions of rows, and real analytics speed.

⚡ Megaladata handles heavy data when traditional tools fail.
🎓 Free Community Edition available to start learning today.

🦈 Leave the Matrix. Take the red pill.