Most smaller companies are going to start with data from relational databases and third-party web APIs. We still want the platform management and security features built into Azure. So, let’s simplify this down to something more reasonable for a smaller company. It is best to not use this service until your companies’ data volume has grown to a scale – where processing it in a timely manner has become a problem. And while it is immensely powerful, this power comes at a steep cost. They build it to operate on a scale that most companies simply do not need. Small and mid-sized companies rarely have the volume of data necessary to justify the use of something like a Dedicated SQL Pool with its enterprise-level capabilities. Which can be provided using the simpler low-cost services available. If you need more frequent updates to your analytics, then consider near-real time with hourly or 15-minute updates. In most cases, daily data updates are more than adequate. A smaller firm should avoid that complexity and cost and build to a slower standard. Much of what they offer and what is possible to use will never be used by smaller companies.įor example, real-time analytics are not needed unless you have dedicated people making minute-by-minute decisions throughout the day. The best approach is to build out an analytics program by taking small incremental steps and grow into more complex data architectures. Cloud-based analytics platforms like Azure provide services for companies of every size and potential use case.Ī small or mid-sized company does not need all this complexity. Where to Start as a Small Businessĭata architectures can be very complex.

By choosing data processing to compute services are based on the lowest cost processing required, they can build a solution that minimizes the ongoing operational costs to the company. It uses the managed data processing and structures of a data warehouse on top of the low-cost storage used for data lakes.įor a small business with a limited budget, the cost of data storage is decoupled from the cost of data processing. This often led to a lack of trust in the data and a loss of benefit to the company.Ī data lakehouse is an architecture that brings together the best elements of data warehouses and data lakes. This is the data that comes from web APIs, web scraping, or other documents not formatted in terms of a relational database.ĭata lakes are great at storing data at a very low cost however, they lack the features available in a processed data warehouse solution. The processing approach emphasized the consistency, integrity, and quality of the provided data, but it can come at a high cost.ĭata lakes arose about 10 years ago to handle data that came in a variety of less structured formats but also desired for analytical purposes.

Typically, the data is coming from databases that have a defined structure and processed into a new database structure optimized for complex queries used in business intelligence. They pull together data from multiple sources within a company for reporting and analysis. Sections:Ī Small Business Data Lakehouse What is a Data Lakehouse?Ī data lakehouse is the combination of two existing analytical data architectures: the data warehouse, and the data lake.ĭata warehouses have a 30-year history in business intelligence.

This approach has become known as the data lakehouse architecture. Over the last few years, people have come up with a similar approach to the choices available for a scalable analytics solution. The cost of the services is not an uncommon issue for many companies. The important thing for a small business to be aware of is that while some of these services have a high price for consumption, we can use others at a lower cost. They bill these services out based on the amount of the service you consume in terms of processing and storage costs. They do not have the deep pockets of large enterprises, so they need to choose the most cost-effective way to create improved outcomes from their analytics.Īll the big players in the cloud-based analytics providers have a broad set of services on offer. Smaller businesses must be able to get the most value possible from their data. Today, even small businesses can gain these benefits with cloud-based analytics services like Azure Synapse. In the past, this required significant investments in hardware, software, and development to achieve. Data and analytics can help all businesses make better decisions, improve customer relationships, and enable strategic initiatives.

Lakehouse architecture