Modern Data Warehouse
Every winning data solution starts with effective data management
With data becoming the driving force behind making important decisions that stimulate organisational growth, it is now more critical than ever that the integrity and accuracy of it is not compromised. Modern data warehouses can store data in various formats, from multiple sources, and bring it together in a unified fashion to derive useful business insights.
Solutions such as the Microsoft modern data warehouse can handle the challenges of big data, apply advanced analytics tools, and deliver real time insights in an efficient manner. Hence, unlocking the true value of your organisational data can be the key difference in attaining an edge in this increasingly competitive landscape – here is why your organisation can benefit from a modern data warehouse:
What is a Modern Data Warehouse?
A modern data warehouse is a unified platform that can store and handle data in multiple forms. By storing data in an organised and easily accessible manner, modern data warehouses enable users to undertake analytics to draw conclusions and insights for reporting. The primary purpose of a modern data warehouse is to undertake analytics and focus on value rather than transactional processes.
Why do you need a Modern Data Warehouse?
With data driving the current business landscape, data analytics and algorithms have become essential to the livelihood and competitiveness of organisations. Data management has drastically changed in the past few years thanks to Big Data and traditional methods of data managements are now unable to keep up with it. Traditional data warehouses often store data locally and undertake inefficient batch reporting to process incoming data which is simply not viable for Big Data. The 3 V’s of Big Data mean that huge volumes of data are being produced daily that encompass many different formats.
Modern data warehouses can meet organisations’ growing needs due to their flexibility and scalability. They can store data in its raw form instead of the previous multilayer formats and handle Big Data whilst providing fast queries so that your staff can quickly perform their necessary tasks. Modern data warehouse’s ability to handle high volumes of data makes them especially useful for the increased adoption of Internet of Things applications where real time data is consistently being generated.
The Antares Approach
We can take the guesswork out of making decisions and help you leverage the power of data to derive key insights. Our approach is simple but viable and ensures you maximise your data assets and underlying infrastructure.
Understanding your business needs
This is the discovery stage where we make sure to deep dive into your unique requirements by identifying your business goals and articulating the current data constraints.
Examining available resources
We assess your organisation’s current data resources including its format, location, and where it is being generated from.
Mapping out current and future state infrastructure
By analysing your current data environment, we can identify gaps and bottlenecks which can be improved for increased operational efficiency. Once the as-is architecture has been recognised, our team defines the data infrastructure that would resolve the challenges and requirements that were identified. We will model the warehouse design so that the data sources, connections, and views are clearly illustrated. Each modern data warehouse design is unique. This means that no two Azure modern data warehouse architectures are the exact same.
User adoption and data governance
Having your modern data warehouse set up is only the first step of your data journey. If your employees opt to not adopt the new technologies, processes, and standards that have been implemented, then you will not see a considerable increase in your data quality. We provide education and training to staff so that they understand how to use data processes and realise the role they play in ensuring data is held to a consistent and accurate standard.
Characteristics of a Modern Data Warehouse
- Capable of handling and processing large volumes of data in various formats
- Governed access and usage of data by authorised users
- Able to manage incoming streams of real time data
- Integrated with various storage technologies and cloud applications
- Support for undertaking a variety of advanced analytics
- Unrestricted access to data for different kinds of users
- Fast processing and monitoring of data for real time access and analytics
- Can evolve to meet changing demands and support multidimensional data models
- Multi platformed architecture that balances performance, scalability, and elasticity
- Supports many users performing actions simultaneously
Traditional vs Cloud Based Data Warehouses
Whilst traditional data warehouses are still able to adequately house structured data for data analytics, they are limited in their architecture and how they accommodate organisational growth. Their lack of scalability and flexibility inhibits an organisation’s ability to keep up with the data that they are generating, and in the long run this can restrict overall performance. Benefits of a modern data warehouse include:
Reduced hardware costs
With cloud-based data warehouses, the third party is responsible for all the hardware, software, support, and maintenance making it a cost-efficient method of storage.
Low entry threshold
As there is no upfront investment needed, organisations can reap the full benefits of elastic storage and scalability with a minimal entry cost. Traditional warehouses required organisations to shell out hundreds of thousands of dollars on servers, administrators and physical infrastructure making it a non-viable option for organisations on a tight budget.
Traditional methods of analysing large data sets would often involve incredible amounts of both computing power and resources, making it difficult and inefficient for evaluation. The beauty of cloud computing is that they are designed to handle data in a variety of formats and process it in a speedy manner thanks to Massively Parallel Processing (MPP).
Data is constantly being produced, at unprecedented speeds, and in a variety of formats. Due to the elastic nature of the cloud, modern data warehouses can accommodate changes in demands so that organisations will not be restricted by limits and miss out on growth opportunities.
Rather than being used for the sole purpose of storing data, modern data warehouses are equipped with the capabilities to undertake data analysis and extract valuable insights. They provide considerable value to organisations by enabling them to quickly and easily understand what’s going on in the current environment and give directions for next steps.
Potential for new insights
Data is power and modern data warehouses have the capabilities to both store and collect extensive volumes of data for analysis. Larger data sets can enable organisations to undertake more advanced forms of analytics such as preventive and predictive analytics which can greatly improve their competitive position. By analysing past trends and forecasting the future, organisations are well positioned to minimise uncertainty and make better informed decisions.
What is Modern Data Warehouse Architecture?
Data architecture is the framework that defines an organisation’s data environment and aligns it with their objectives and needs. It standardises and governs how data is captured, stored, transformed, and used by the relevant users. Modern data warehouse architecture delivers a flexible and adaptable data ecosystem that automatically detects and responds to changes and enables organisations to quickly locate and distribute their data across an array of storage technologies.
Components of Microsoft Modern Data Warehouse Architecture
Azure Synapse Analytics is the scalable, cloud-based enterprise warehousing solution offered by Microsoft that uses the power of MPP to streamline the entire data journey from ingestion to transformation to preparation. Its integration with Power BI and Azure Machine Learning gives organisations the elasticity to process large volumes of data on demand to gain valuable insights.
Azure Data Factory is a cloud based ETL and data integration platform that allows you to workflows that facilitate the movement of data between data stores. By integrating the data residing both on premise and in Microsoft SQL Server, users are provided with a singular point of view into their ETL pipelines.
Azure Blob Storage is a scalable storage service used to cache Binary Large Objects (BLOBS) allowing you to access unstructured data when needed for analytics. This low-cost storage option is perfect for media types such as texts, videos, images, and logs.
Azure Databricks is an Apache Spark based data analytics platform optimised for Microsoft Azure that enables users to collaborate on tasks in a shared workspace.
Azure Analysis Services is a platform as a service offering from Microsoft that includes a range of managed services that can enable organisations to consume and process data using a wide variety of technologies. Users can create tabular models and conduct data analysis using intuitive tools such as Power BI, Excel, and Tableau.
Power BI is a business analytics tool that allows users to create dynamic visualisations and beautiful reports that can be accessed from any device at any time. It pulls data from multiple sources and transforms them into actionable insights that can be viewed as easily comprehensible graphs.
As a Microsoft Gold Partner in Data Analytics, we have the experience to help your organisation unlock the true value of data. We can create flexible architectures such as modern data warehouses in Azure that can seamlessly ingest, store, process, and analyse data in various formats to deliver actionable insights. Contact Antares to discover how you can maximise your data assets and streamline your journey from ingestion to consumption.
What are the Characteristics of Modern Data Warehouse Architecture?
- Automated: Modern data warehouses automatically profile and tag data as it enters the system through a process called metadata injection. As data flows continuously into the warehouse, data cataloguing kicks in to sort the data, detect changes and anomalies before alerting the relevant individual of the irregularity.
- Real time data: Organisations need the latest data to make the most informed decisions. Outdated insights produce expired decisions which do not meet the current changes and needs of the external environment. Modern data architecture can encapsulate real time data and perform validation, classification, and management automatically so that organisations can leverage the most up to date insights to support their business decisions.
- Collaborative: Unlike traditional data architectures which required the IT department to be responsible for all aspects of data related procedures, modern ones allow individuals from different business units to access and use data as they need. Data analysts and data scientists can prepare reports and undertake analytics as required without having to funnel procedures via IT.
- Governance: Modern data architecture revolve around the idea of self service and define different levels of authority according to user roles and needs. Each user type is assigned a level of permission so that they can gain access to the data necessary for them to carry their tasks out but automatically locked out of entry for anything beyond that.
- Elastic: In the age where data rules everything, organisations need an elastic architecture that can accommodate and adapt to changing data requirements. Modern data architecture allows organisations to benefit from on demand scalability at affordable prices without having to shell out grand amounts for upfront investments.
- Data integration: The beauty of modern data architecture is that it can integrate with existing legacy applications without the need for replacements. You can continue to use your pre-existing systems and enable data to be easily optimised for sharing across organisations and locations.
- Secure: Modern data architecture provides ready access to authorised individuals whilst also keeping unwanted threats and intruders at bay through data encryption. By masking sensitive data and tracking audit trails, organisations are better protected against hacks and security breaches.
- Resilient to changes and demand: With data residing in the cloud, modern data architecture needs to be resistant against server outages and disasters. Many cloud providers offer disaster recovery options and data backup capabilities so that your data is proofed against potential threats and risks.
Modern Data Warehousing Options
Infrastructure as a Service
IaaS is a form of cloud computing that requires the provider to manage all the hardware and infrastructure whilst you purchase and configure the software. This model enables organisations to cut costs and enjoy the flexibility required to accommodate changing demands in data.
Platform as a Service
Just like IaaS, PaaS uses a pay as you go model whereby organisations are able to access data warehouse services via an internet connection. The service provider delivers a complete platform for developers to create custom software and hosts everything – servers, storage, hardware – whilst the customer is responsible for managing their own data and applications. This option is perfect for organisations looking to develop software unique to their own needs without shelling out grand amounts and undertaking the heavy lifting.
Software as a Service
The SaaS model allows organisations to access a complete software solution via an internet connection. The cloud provider is responsible for the maintenance of all the underlying infrastructure, hardware, software, data, and applications. Organisations are able to get up and running quickly with this model with minimal upfront costs or effort.
Not sure where to start with your modern data warehouse journey? Antares can help you determine the right architecture and data model that can help you achieve your organisational goals. As Microsoft Gold Partners, we have the experience in delivering modern data warehouses that meet your needs, enable you to perform data driven decisions, and improve your processes.