Implementation of Azure Data Lakehouse architecture: 2-hour briefing

Due to the constant growth in the amount of data and requirements for the speed of their processing, companies need new approaches to storing and processing data.

Data Lakehouse is a new data management architecture that combines Data Warehouse and Data Lake. Data Lakehouse combines the flexibility, cost-effectiveness, and scalability of data lakes with the data management and transactions of ACID data warehouses. The architecture provides Business Intelligence (BI) and Machine Learning (ML) for all data.

As part of this offer, a 2-hour meeting will be held with specialists from your company. At the meeting, we will discuss possible scenarios for building a Data Lakehouse architecture and determine which approach is most relevant to your tasks.

At the meeting, we will discuss the key advantages that using Data Lakehouse provides:

• Flexibility in working with data
  Data Lakehouse allows you to store data in different formats, including unorganized and prepared for analysis, directly in Data Lake.

• Big Data processing

Data Lakehouse architecture increases the speed of processing large volumes of data (Big Data) thanks to distributed processing, horizontal scaling, and the use of technologies such as Apache Spark.

• Real-time data processing

Data Lakehouse supports real-time data processing, allowing analysts to obtain relevant information and make decisions in real time.

• Single point of access

Data is stored in a Data Lake and is available for analysis and reporting using various tools. This provides easier and faster access for all users.

• Price

Data Lakehouse reduces data storage and processing costs by using Data Lake to store unorganized data, reducing the need for pre-structuring and indexing.

• ACID transaction support

Data pipelines are capable of simultaneously reading and writing data. Support of ACID (Atomicity, Consistency, Isolation, and Durability) transactions ensures consistency as multiple parties simultaneously calculate or write data, typically using popular SQL query toolkit.

Support of various programming languages

Using both SQL and different programming languages when processing data.

• Multicloud

Ability to use data from any Azure, AWS or GCP cloud environment.

As a result of the meeting, you will understand the key capabilities of the solution and further steps to implement the Azure Data Lakehouse architecture.

By choosing SMART business, you get the expertise and experience of our analytics and data specialists.

Our advantages:

• Data is protected by a non-disclosure agreement (NDA).

• All rules and Guidelines for Microsoft CSP partners are followed.

• Zero trust model and MFA (multi-factor authentication) are used for all tools.

• SMART business meets all the requirements of ISO/IEC 27001:2013 and ISO 9001:2015 international standards and has appropriate certificates.