The business world is awash in data. Be it of the qualitative or quantitative variety, discrete or continuous data, companies rely on all types to help them make more informed decisions, evaluate performance, establish goals and identify areas of improvement, among many other business-related purposes. And there is a ton to draw from. In fact, it’s estimated that there are at least 400,000 bytes of data for every grain of sand in the world. Organizations have collected a lot of it, but the vast majority – perhaps as much as 73%, according to Forrester Research – winds up on the cutting-room floor, having never been analyzed. Unvetted data opens the risk of it being lost, mishandled or corrupted, which prevents stakeholders from putting it to valuable use.
Data warehouse solutions help to solve this issue. Here, we’ll discuss what a data warehouse system is, the industries that use them, the benefits of data warehousing, how they compare and contrast to data lakes and how data warehouse software helps improve data quality.
What is data warehousing?
Data warehousing is the process of using technology, analytics and reporting systems to collect, manage and store data from multiple sources, even if they have no association with one another. The warehouses themselves are centralized repositories that are typically cloud-based and the data may be historical or current. The cloud data warehouse enables business leaders and stakeholders to access data on an as-needed basis while being in a secure cloud environment. Accessing the data involves using business intelligence tools to analyze, report mine or conduct reporting. In addition to the cloud, a data warehouse can be deployed in an on-premise or hybrid environment. As their title suggests, a hybrid environment is part on-premise and part cloud. Businesses that seek to migrate to the cloud – but aren’t quite ready to do so fully – frequently opt for a hybrid deployment to ensure a smooth transition.
Why are data warehouse solutions so important?
“Data” and “information” are terms that are frequently used interchangeably. But data is only information if it can actually be put to use to foster learning or divine insights about internal or external factors. When data is left out in the ether, or maintained in detached information silos, it can be difficult to derive any meaning from it, running the risk of the data being corrupted, lost or modified.
What data warehousing does is translate data to make it more easily accessible by running various analyses that help to offer a deeper level of understanding for the people who are using the data. Since a data warehouse ensures all the data is cleansed and stored securely, data quality is virtually guaranteed. This means stakeholders can trust the data that they’re drawing from to guide their decision-making or to identify trends. In this way, a data warehouse facilitates knowledge.
What are some of the other motivations for a business to use a data warehouse system?
Big data is big business. Because there is so much to be drawn and learned from data, organizations in every industry take advantage of data warehousing infrastructure. In 2019, the global data warehousing market was worth nearly $21.2 billion, according to Allied Market Research. By 2028, its valuation is projected to more than double, topping $51 billion.
Here are a few of the reasons why so many businesses and enterprises nowadays use data warehouse software:
Helps to standardize data: As previously noted, data comes in a wide variety of different formats and types, much of it in its original state. This is otherwise known as raw data. Raw data can provide valuable context into how data was collected, which can help ascertain data quality, but not much beyond that. A data warehouse enables business leaders to glean actionable insights from their data because it’s been standardized and defined into a common and consistent format, even though the data may come from entirely different sources that are unconnected to one another. Those sources may be the cloud, enterprise resource planning software, on-premise databases, a data lake or other data collection vessels.
Make more informed decisions: Running or managing a business involves a litany of choices – some of them pedestrian, others highly consequential. A study from Cornell University suggests the average adult – business owner or otherwise – makes more than 35,000 decisions per day. The best choices are those that draw from insight, reflection and observation, but as mentioned earlier, much of the data companies collect is never examined. A data warehouse is able to methodically analyze and interpret massive volumes of data quickly so business leaders have the full context they need to decide on the right path forward.
Offers a competitive advantage: In the immortal words of Sir Francis Bacon, knowledge is power. When business leaders have access to more data than those of their competitors – thanks to their enterprise data warehouse storing new and historical data from heterogeneous sources – it gives them highly valuable information on their market, customers or trends that others may not know about. This allows them to take action or to recalculate if the data suggests a certain approach may be inadvisable.
Cost-effectiveness: The very idea of maintaining massive volumes of data in separate silos – never mind actually doing it – is the epitome of inefficiency. That’s especially true when one of those data storage methods is on-premise infrastructure, which entails ongoing maintenance, space, manual updates and data backups. The labor intensiveness and technical aspects of it all often require hiring an IT specialist. Since a data warehouse is centrally located and in the cloud, much of the maintenance a cloud data warehouse entails is done automatically, which reduces the cost of labor.
Fully scalable: Much like the size of your business can change, so can your data needs. Should you need to collect and analyze more of it over time, a cloud data warehouse can scale up or down. Its elasticity is what makes a cloud data warehouse the ideal solution for companies of all sizes.
Is a data lake the same thing as a data warehouse?
A data warehouse has many defining characteristics, from facilitating data storage to serving as a one-stop source for effective data management. Perhaps its most defining one is the fact that it’s a centralized repository for holding data that’s culled from many different sources.
A data lake checks off this same box, which can lead some to believe that a data lake and a data warehouse are distinctions without a difference. While they are indeed used for similar purposes and feature a number of corresponding functionalities, there are a few ways in which they differ. Knowing how they compare and contrast can help you avoid making a decision about whether your data management strategy may not meet your needs.
Type of data that is stored: The structure of the data held in a data warehouse versus a data lake is the most fundamental difference. While a data lake typically houses raw data – which hasn’t yet been processed and is unstructured data – a data warehouse stores structured data. Structured data means that it has been processed, which makes it immediately ready for analysis or queries.
Desired use of data: In a data lake, the data is undefined, which means that no purpose is attached to it. A data warehouse parses and filters data via batch processing, so the data is both defined and applied for a specific need.
Users: Raw or unstructured data, which is maintained in data lakes, tends to be used by data scientists, data architects, machine learning engineers and other professionals who specialize in data. Their background and expertise in data science enable them to know what to do with the data despite its raw state. Non-specialized business people leverage data in data warehouses because the purpose of the data has already been defined.
None of this is to suggest that a data warehouse or data lake is better than the other. Depending on what kind of business you run and the industry you’re in, you may wind up using both of these data management sources. However, if the data you collect is intended for a specific goal that is clearly defined, then a data warehouse solution makes the most sense.
In a similar vein, a data warehouse is different from a database, even though they both serve as gathering places for data. Whereas databases are for the recording and retrieving of data, the primary function of a data warehouse is analyzing data in large quantities, namely big data.
What kinds of businesses use data warehousing?
Since data is everywhere and stands to benefit any organization that collects and leverages data analytics, data warehousing is and can be used by any company, government entity or institution. These include:
- Colleges and universities
- Pharmaceutical developers
- Food producers
- Federal government
- State government
- Local government
- IT developers
Banks and credit unions also use data warehouses for a variety of needs, one of which relates to personalizing the banking experience for their customers. Mobile applications and broadband internet access have revolutionized how people go about their banking-related activities, from depositing checks instantaneously via their smartphones or checking their balances on their financial institution’s website. Steve Wilson, a financial guru and founder of the website Bankdash.com, told BAI that data provides financial institutions with tremendous insight into how customers use their money. As such, they can “sift through transaction data to uncover spending trends … make use of bank transaction data, credit behavior data and location data and correlate it with a set of suggestions and advice.”
This kind of defined data makes it ideal for use in a data warehouse environment.
Product development is another way in which banks regularly take advantage of data. As tech expert Matt Tengwall related to BAI, when clients or customers make significant purchases, it’s often related to a major life event or milestone. Studying particular types of customer data, like spending habits during a particular time frame or lead up to a ceremony, provide financial institutions with insight on what products would be worth introducing that serve their customers’ needs for that life event.
Since historical data is stored within a data warehouse, financial institutions can glean insights on what products might make sense to offer based on the buying trends of customers in similar life situations.
Health care providers also take advantage of cloud data warehousing. Whether it’s medical offices analyzing the performance of their attending physicians, identifying health outcomes in patients after they’ve been discharged, resource allocation or determining the cost-effectiveness of care, data warehouse software helps businesses of all kinds make smarter decisions about how they operate.
From affordability to business intelligence, the benefits of a data warehousing solution and data warehousing software are boundless and make it self-recommending. But if you’re not an IT specialist nor employ data scientists, you may not know how to put one in place. Leave the technicalities to us at Solvaria. For a quarter of a century, Solvaria has provided world-class data warehousing, data migration and data management capabilities to organizations in manufacturing, tax preparation, energy forecasting, health care and more throughout the country. If you have the data, we can make it work for you better. For more information on our solutions, please contact a Solvaria expert. Better service starts here.