Data Warehouse Overview
All about the data warehouse, start here to find out more
What is a Data Warehouse
A data warehouse is a centralized repository that stores data from multiple sources, making it easier to analyze and generate insights.
The key features of a data warehouse are:
- Integration: Combining data from various sources into a single, unified view.
- Historical Data: Storing large amounts of historical data for trend analysis.
- Query Performance: Optimizing data retrieval for faster query performance.
- Data Quality: Ensuring high data quality through cleansing and transformation processes
Learn more….What is a Data Warehouse
Why you need a Data Warehouse
The importance of having a data warehouse and its advantages and disadvantages. Key points include:
Advantages:
- Better Decision Making: Integrates data from multiple sources, providing a comprehensive view for informed decisions.
- Improved Performance: Handles large amounts of data efficiently, enabling complex queries and timely results.
- Data Integration: Combines data from various sources into a unified view.
- Historical Data: Stores long-term data for trend analysis.
- Scalability: Can grow with your data needs.
Disadvantages:
- Complexity: Can be challenging to set up and manage, especially with diverse data sources.
- Data Silos: Poor integration can lead to isolated data pockets.
- Cost: Initial setup and maintenance can be expensive.
Learn more…Why you need a data warehouse
Which Data Warehouse is best for you
How to choose the best data warehouse for your needs.
There are several key factors to consider:
Key Factors:
- Technologies and Skills: Choose options that fit with the technologies and skills your team already has.
- Implementation Costs and Timescales: Consider the budget and time required for setup.
- Scalability: Ensure the data warehouse can grow with your data needs.
- On-Premise vs. Cloud: Decide whether to host the data warehouse on-premise or in the cloud.
- Compliance Requirements: Make sure the solution meets any regulatory requirements.
- Operational Costs: Factor in ongoing maintenance and operational expenses.
Types of Databases:
- Relational Databases: Commonly used for structured data, easy to use, and support a wide range of queries (e.g., SQL Server, Oracle).
- NoSQL Databases: Handle large amounts of unstructured data, more flexible and scalable (e.g., MongoDB, Apache HBase).
- Column-Oriented Databases: Optimized for fast query performance, store data in columns (e.g., Amazon Redshift, PostgreSQL).
- Cloud-Based Databases: Hosted on remote servers, cost-effective, and scalable (e.g., Microsoft Azure, Google BigQuery).
Learn More…Which Data Warehouse is best for you?
Differences between a data lake and a data warehouse
Here are the key differences between a data lake and a data warehouse
Data Lake:
- Data Type: Stores raw data in its original format, including structured, semi-structured, and unstructured data.
- Purpose: Used for big data analytics, machine learning, and real-time data processing.
- Schema: Applied after data storage, offering flexibility and agility.
- Users: Data scientists and engineers who need to perform in-depth analysis.
- Accessibility: Easy to update and modify.
Data Warehouse:
- Data Type: Stores processed and structured data.
- Purpose: Used for business intelligence, reporting, and analysis.
- Schema: Applied before data storage, ensuring high performance and security.
- Users: Business professionals and analysts who need structured data for decision-making.
- Accessibility: More complex to update and modify.
Lean more…Differences between and data lake and data warehouse
Data Warehouse Technologies
An outline of some of the technologies available
SQL Server
A relational database management system (RDBMS) known for its robustness and scalability. It has the ability to handle complex transactions, large data volumes, and high-performance workloads, making it suitable for both small and large applications
Microsoft SQL Server – Select Distinct Limited
Google Big Query
A fully managed, serverless data warehouse designed for large-scale data analytics. BigQuery allows users to run super-fast SQL queries using the processing power of Google’s infrastructure. It is highly scalable and cost-effective, making it suitable for analyzing vast amounts of data in near real-time
What is Google BigQuery – Select Distinct Limited
Snowflake
A cloud-based data warehousing and analytics platform. Snowflake allows organizations to store, manage, and analyze large volumes of structured and semi-structured data. It is designed to be highly scalable, secure, and efficient, with a focus on performance and ease of use
Snowflake Data Cloud – Select Distinct Limited
Our Data Warehouse Consulting
Data Warehouse Consultancy services.
We specialize in designing and building data warehouses that consolidate and organize data from various sources. Our approach includes data integration and transformation using best practices and tools for data extraction, transformation, and loading (ETL).
Our consultancy aims to help businesses turn their data into actionable insights, improving decision-making and overall business performance. Whilst empowering your team, helping them to learn and understand the technologies and drive your business forwards
Customer Testimonials
We can put you in touch with our happy customers who have found our Data Warehouse Consulting really valuable
Not content with showing you irrelevant case studies. We prefer to refer you to happy customers that we have helped that had a similar situation to you
Some examples of Our Work
We have examples from Wholesale, Retail, Facilities Management, Security, Sport, Food Manufacturing and much more
Frequently Asked Questions
How do we get started?
We recommend starting with an initial FREE call to explore what the best options are for you. Rather than one solution fits all we like to learn about your needs and current capabilities and then work the best way for you
How long does it take?
Getting the best from your business data should be part of your overall business strategy. We can help with reviewing your strategy through to implementation and training. From long term projects where me maintain regular touch points and help you on your journey, through to short specific projects we can support anything in between, from 5 days to 12 months +
Which Data Warehouse technologies do you work with?
Our core focus in on market leading products such as Microsoft SQL Server, Google BigQuery, Snowflake
Microsoft Fabric, Databricks and AWS
We do also work with other tools from time to time
Which data sources can you work with?
Anything from raw text files, spreadsheets, JSON through to SQL databases and on to integrations with back end systems using API connections
Do you offer Business Intelligence training?
We find that the best training is when the training material is using your company data as context is very important in business intelligence. We prefer to help you create tailored content for your users using your business data
From beginners through to more advanced techniques we have delivered training. But one of our more popular options is our mentoring where we have regular touch points. These help your users solve their reporting challenges with our remote support support
This one to one mentoring helps our consultants to really understand your needs and help to develop your skills
What size of project do you undertake?
From the small, light touch consultancy through to in depth design and build we have the depth of knowledge to support and broad range of projects
Variety in our service offering makes the projects enjoyable and varied
Our personable consultants are skilled in keeping it simple for you, using plain English to explain everything and go out of our way to make sure you are left with no knowledge gaps
Book Now to reserve our consultants availability
