Get advice

Business solutions based on Data Warehouse data

We are introducing shared storage (DWH) for analytics and data exchange in the enterprise. Data Warehouse allows you to quickly receive regular reports and more easily collect new reports based on a hypothesis. It also helps reduce integration support costs.

Get advice

You'll also get

Popular comparison table  DWH tools

DWH data helps you make effective decisions in areas

Retail

Production

Construction

Fintech

logistic

Medicine

Pharmaceutical industry

Many others

Enterprise shared data warehouse
(Data Warehouse) allows

Implement a Data Driven approach

Learn more about the DATAREON ESB platform - KT.team

With the DATAREON ESB platform, new applications are easily integrated into the architecture - KT.team

The Data Driven approach is a method of making decisions based on objective data and analytics, rather than based on intuition, expert opinion, or tradition. It allows companies to use their data to identify trends, understand customer needs, and forecast future events.

Data Warehouse houses structured data from across the enterprise. This way you can easily and quickly build any reports for making decisions.

Reduce integration support costs

DWH implementation begins with the development of fault-tolerant integrations. We are creating separate connectors that work independently.

With the help of integrations, DWH gets data from the entire enterprise in raw format. Such data can be consumed by both BI and the services themselves — ERP, PIM, etc.
‍
Data exchange via DWH reduces integration support costs, ensures reliable data exchange and flexibility to change.

Get regular reports faster

Generate regular reports quickly - KT.team

Regular storefronts are formed on the basis of raw data. The data in them is updated at the required frequency. For example, once a day.
‍
Analysts will be able to receive reports faster because BI uses already prepared data from their regular storefronts.

Test hypotheses point-by-point

Simple hypothesis testing with ad-hoc showcases- KT.team

At the third level of DWH, showcases are created on demand for a specific hypothesis. This way the marketing department and sales department will be able to A/B test hypotheses  and draw more accurate conclusions.

Get a free consultation with an expert

Submit a request

We will define the boundaries of the problem that causes losses to businesses

We will develop possible solutions and tools for their implementation

We will define the implementation plan and the next steps

You can implement this solution with us, another integrator or your team

Examples of hypotheses and their metrics

Find solutions to business issues, formulate and test hypotheses with clear metrics and accurate data.

Business questions

Hypotheses, ideas

Trackable metric

How to increase product sales on the site?

Items that start with emojis sell better.

Converting views to sales

How can we improve customer retention and loyalty?

The introduction of a repeat purchase bonus can encourage customers to return.

The share of repeat sales

What would be the most profitable product price?

An increase in the price of product "A" will increase its overall profitability.

Sales profitability

How to improve the efficiency of the retail chain?

Changing the store's design can increase sales with the same traffic.

The average customer's check at the store

How to reduce the cost of transporting and storing goods?

To switch to the just in time model, you need to understand when to buy goods.

The level of turnover of goods

Our approach
and benefits

Risk Free. If you are unhappy with the result, you don't have to pay for the work. We specify this clause in the contract.

Alienation. We don't hold customers hostage. All our solutions are easy to share with your team or another contractor.

Efficient IT. For us, IT is effective when it brings results for business and ensures a high rate of change.

Expertise. 400+ successfully launched integrations on various tools (Kafka, MuleSoft, WSO2, etc.).

Control. Each integration we have launched is under the control of the monitoring system.

Implementation steps

We have designed the implementation process so that you get the most out of it. You can go all the way with us. Or order any of the steps separately and hand over the rest to your team.

1. The boundaries of the DWH system have been formed

sample scenarios for using DWH have been identified;
the current and desired reports used by BI were analyzed;
an analysis of data sources, the volume and composition of data from them was carried out.

2. Technical specifications for storage have been generated

a composition of showcases has been formed on the basis of which business unit dashboards are built;
scenarios for their aggregation from the raw data warehouse have been recorded for showcases;
the composition of raw data warehouses has been determined;
database schemas are described;
the sources of raw data and the procedures for uploading them to the repository have been identified;
tools have been selected for creating showcases and raw data warehouses;
procedures for validating and ensuring data quality are described.

3. The project has been implemented

your BI system uses data only from DWH;
DWH can be easily improved not only for BI and analytics, but also for integrations;
DWH is poised to become the only source of truth in data for consumer systems.

Get a comparison table for DWH tools

We compared popular tools for implementing DWH. For example, Hadoop, PostgreSQL, ClickHouse, Greenplum, etc. The result is presented in a compact table. Submit a request and get the file for free.

Submit a request

A team of practitioners,
not theorists

The continuous development and training of the team is embedded in our processes. The qualification department, leading developers and managers are constantly updating and improving training practices. We do not allow employees who have not been successfully trained in key practices to participate in projects.

110+

experienced
specialists on staff

50+

average customers
and big businesses

30+

implementation projects
integrations

10+

years of practice
and successful cases

They trust us

Get a free consultation with an expert

Examples of hypotheses and their metrics

Implementation steps

1. The boundaries of the DWH system have been formed

2. Technical specifications for storage have been generated

3. The project has been implemented

Get a comparison table for DWH tools

They trust us

KT.Team Maxxium

KT.Team La Nature

KT.Team St Gobain

KT.Team Твое

KT.Team SQ 2

KT.Team SQ 1

KT.Team Norgau

KT.Team Музторг

Рабочая тетрадь Саблуков

Рабочая тетрадь Серветников

KT.Team Brandly

KT.Team Трансатлантик

KT.Team FML

Рабочая тетрадь Шилов

We helped to reduce the load and scale system throughput

We redesigned the IT architecture and drew up a roadmap for its transformation

Integration of Talend ESB into the IT infrastructure of a logistics company

We have developed a targeted system integration scheme. We implemented ESB technology and launched 48 streams

We provided Polaris with the ability to easily bring new products to marketplaces

We have implemented a scalable service bus for ATIMO

Work with product data has been automated for the Fix Price network

Connect 1C to the data bus via a ready-made module

Cases

We redesigned the IT architecture and drew up a roadmap for its transformation for music retailer Muztorg

Integration of Kafka into the project's enterprise infrastructure

We provided Polaris with the ability to easily bring new products to marketplaces and change product information in a few clicks

Let's discuss your project