Businesses that want to build large-scale, effective data strategies will want to collect and store large amounts of information. To compete with other data-driven businesses, organizations need to shift from passive data collection to active data management.
The average business can have a dozen or more different data sources, depending on their size, industry, and internal organization. With all these data sources, a business might collect thousands of rows of data in a day.
Over time, if a business wants to store this data, the scale of their data storage causes problems. A business can’t effectively use spreadsheets to manage their data when their data sets are millions of rows long.
In addition, smaller data storage solutions are often siloed. This means that the data from one data source can’t be viewed or combined with other data. It also means users who work with one data source can’t usually access others.
To manage their data in an effective way, businesses need better data storage solutions. They need a solution that can both handle data at scale and aggregate all of their data into one centralized, accessible location.
Data warehouses are how businesses can solve their data collection, management, and access problems. They allow businesses to manage their data in one place, so that it can be more easily used for business operations.
Businesses that are struggling to manage their data should look at data warehouses as an agile and robust solution for data storage. Coupled with the power of modern business intelligence tools, a data warehouse can transform a business’s data strategy.
What is a data warehouse?
A data warehouse is easy to understand but more difficult to actually implement. A data warehouse is one centralized data storage location where all business data is collected and stored.
These types of tools connect to your data sources through integrations, collect data as it’s generated in real time, and then store that data. From there, the data can be used for analysis and visualization.
Data warehouses are a part of a business’s larger data infrastructure. Data infrastructure is the name for the systems businesses use to collect, manage, and store their information.
For most businesses, their data warehouse is the core of their data infrastructure. It sits at the center of their data implementation, taking in data from data sources and communicating it out to other tools.
Why does my business need a data warehouse?
A data warehouse isn’t just nice to have. It fills real needs that businesses have related to their overall data strategy.
First, data warehouses streamline data access and organization. One problem that businesses often face when they start to grow their data strategy is how to organize and facilitate access to data.
When businesses organize their data in ad hoc, informal ways, then it becomes very hard for anyone to actually find the information that they need. People can’t use their data for insight if they have no idea where that information is stored.
Data warehouses allow businesses to store their data in clear, consistent, and centralized ways. Users know where to find their data—at the very least, they know it’s in the data warehouse.
From there, data can be organized at a deeper level so that data workers can more easily find the sort of content they need to perform analytics and build their visualizations.
Second, data warehouses prevent data silos. Data silos happen when business data gets trapped in a place where it can’t easily be used.
Sometimes, data silos happen when tools can’t communicate, but more often, they represent a failure of internal business communication. Teams and departments don’t think to share their data, which leads to their insights being siloed.
Data warehouses help to manage this by streamlining and simplifying data sharing procedures. Now, instead of having to send out spreadsheets or hand out access, managers of a specific tool can just connect to the data warehouse to make their data available to all.
Third, data warehouses are essential for big data analytics. As businesses grow, they start to collect more data, and soon, their data sets start to overwhelm their basic data storage strategies.
However, businesses need these big data sets to effectively make decisions. The larger a data set is, the more accurate it is for providing insight into business operations. To get the most effective insights possible, businesses need to leverage the power of their big data sets.
That means they need data collection and storage solutions that can manage data at that scale. Data warehouses are the first choice for this use case; they’re specifically designed to handle data storage at this level.
Big data isn’t just useful for getting more accurate insight. It’s also essential for advanced analytical techniques like predictive analytics and machine learning. Data warehouses make leveraging these techniques possible.
What do I need in a data warehouse?
There are all sorts of different data warehousing solutions on the market, from small-scale file sharing networks to enterprise-scale, standalone data infrastructure management systems.
The challenge for businesses, then, is to figure out what sort of solution will serve their business the most. For many businesses, this is easier said than done.
Your ideal data warehouse will depend on your industry, the scale of your data, and how much you’re willing to pay. However, there are some guidelines you can use to make sure you’re getting your money’s worth.
Good data warehouses are cloud-based. That means they’re not stored on your internal network or personal computer—they’re stored on a third-party server that you can access through the Internet.
Not only does this make data access easier, since you’re not tied to one specific device or network, it also makes connecting to other cloud-based data sources easier. Trying to connect to on-premise software is difficult, and it’s best to avoid it if you can.
Of course, there are some situations where an on-premise data warehouse is valuable. For example, hospitals and other medical businesses that store patient data are heavily regulated in how they can access and store that data.
In that case, they may not be able to hand over their data to a third party, making cloud-based data storage solutions impossible. For these businesses, an on-premise data connector may be effective.
Federated data solutions
Sometimes, businesses don’t want just one layer of separation between their data sources and their data visualizations. Data warehouses act as a valuable bridge, but sometimes, businesses can extract even more value by making their data storage slightly more complicated.
For example, imagine a mid-sized business where every user needs to query their data warehouse whenever they need information. Depending on the size of the company and their data demands, this could mean multiple data requests a second.
Data requests at that scale can slow down even powerful data warehouses. Larger businesses need some way to manage access to their data warehouse while still connecting users with the data they need.
This is where federated data infrastructure can be helpful. In a federated system, there are more layers of organization and storage between the data warehouse and the end user.
There are many different ways that a business can federate their data warehouse. They can implement data marts, which store information relevant to one business sector. Users can access their data marts instead of their data warehouse, lowering the strain on the remote server.
BI as a data warehouse
Data warehouses can be a valuable tool, but all but the largest businesses can’t manage the cost of a robust, standalone third-party data warehouse. Most businesses need to think about other data warehousing solutions.
Many businesses in this situation already have a business tool that can connect to data sources, collect data automatically, and store it in a central location. A BI tool can do all of this and more.
Larger businesses with truly massive data requirements might want to look at third-party data storage solutions, but many businesses can save costs and streamline their processes by using a BI tool for data warehousing.
Data warehouses—making data storage easy
Businesses can’t use ad hoc solutions to manage and store their data. Data analysis and visualization might lead to the most tangible results, but data infrastructure is just as important to overall success.
Data warehouses are essential for data infrastructure success. They help businesses manage their data strategy. They remove data silos, facilitate big data analytics, and make data access simpler.
Organizations that are struggling to manage their data in an effective way need to invest in a data warehouse. They can invest in a standalone tool or shortcut it all and use BI to power their data warehouse success.
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