Data Warehouse: Characteristics and Benefits

With each passing day, we accrue more data than ever. In the digital era, data warehouses are shaping up to be business-critical processes.

Neville Kroeger
Neville Kroeger, September 19, 2017 3:15 pm
Blog > Data Warehouse | Data Automation | Database > Data Warehouse: Characteristics and Benefits

Do you struggle with data warehouses? Are you baffled by the benefits they offer? Can you tell the difference between a ‘database’ and a ‘data warehouse’? While the scope and scale of data warehouses may be a little overwhelming, at the end of the day they’re fairly simple to understand, and when used correctly will be a critical business component.

The Globalization Conundrum

As the business world gets bigger and more interconnected, it can sometimes feel as though the globe itself has shrunk. Most major conglomerates are now international organizations, operating in some form or capacity on each and every continent. Take the Coca-Cola Company, for instance: as the world’s biggest soft drinks firm, its products can be found in almost every food and drink store on the planet. To try and put its scale into perspective, on average Coke sells almost 1.9 billion servings of its products - daily. Its customer base is nearly unfathomable.

But as companies grow, they run the risk of becoming alienated from their client base, not only geographically, but also culturally. This can lead to missed opportunities and revenue, and as such, organizations are increasingly looking to data for answers, with most already operating stores, offices and outlets in countries all over the world, each generating huge amounts of data.

Gathering this information is all well and good, but many firms are struggling with their attempts to put this collected knowledge to any meaningful use. Why? Because there’s so much of it. Indeed, you don’t have to be a Coca-Cola-scaled company to generate a mindboggling level of data; far from it.

Over the course of just two years (2015-2016), more data was created than in the previous 5000 years of humanity combined. Want to go a level further? In 2017 alone, analysts are expecting the level generated to exceed this. There’s never been more data available than right now, yet tomorrow’s data will dwarf today’s.

Data’s continued exponential growth poses something of a paradox: the more data we have, the greater our chances for conversion – but due to its volume, increased data becomes more problematic for effective analysis. How does one even go about simply storing this material, let alone begin to analyze it? Data warehouses are key to solving this paradox.

Breaking Down the (Data) Warehouse Doors

Simply put, data warehouses are repositories of high-volume information. They are centralized stores of all the data a company may generate, formed by relational databases and designed for query and analysis. Data warehouses allow for quick, accurate access to structured data via predefined queries.

There are three prominent data warehouse characteristics:

  • Integrated – The way data is extracted and transformed is uniform, regardless of the original source
  • Time-variant – Data is organized via time-periods (weekly, monthly, annually etc.)
  • Non-volatile – A data warehouse is not updated in real-time. It is periodically updated via the uploading of data, protecting it from the influence of momentary change

Utilizing data warehouses makes it simple to generate reports, run ad-hoc queries and extract near-limitless streams of data that can be converted into meaningful business data.

The data warehouse’s greatest strength is getting relevant insight and information into the hands of decision-makers in a timely manner. This enables businesses to keep up with the pace of change, high-competition and digital transformation.

Database or Data Warehouse?

  • Databases are real-time repositories of information, which are usually tied to specific applications
  • Data warehouses pull information from various sources (including databases), with a focus on the storage, filtering, retrieval and, specifically, analysis of huge volumes of structured data

I find this to be an effective way of summarizing the differences: imagine you are a customer at both Shop A and Store B and the two separate companies have recently merged, becoming Retailer C.

Before the acquisition, both retailers had gained various levels of data about their customer base, purchase and return histories, contact details, personal address, items viewed but not purchased, etc. All of this information is stored in traditional databases and independent of the other’s.

Now, as Retailer C, the newly merged company adds a data warehouse, which draws in all of the above data ­– from both databases, enabling thorough analysis.

By being able to collate all this disparate data into one location, the retailer can now analyze this information in depth to discover patterns in its customer’s buying habits and suggest similar products, for example. They may even find key shopping trends in specific locations, which could be of interest to regional customers.

By bringing all this data together, the retailer can offer the customer products they may be interested in, widening their funnel for potential conversion.

What are the Data Warehouse Benefits?

For me there are three main benefits to utilizing a data warehouse:

1) The enablement of better decision making:

As companies are now able to get closer to their consumers than ever before, the corporate decision-makers no longer have to hedge their bets, or make important business decisions based on partial or limited data. They’re now backed up by facts and statistics housed within data warehouses that can be recalled ad hoc.

2) Quick and easy data access:

If there’s one thing the application economy has taught us, it’s that speed is everything. Users can access an array of information, stored across multiple sources, almost instantly. It means you won’t be wasting time attempting to manually pull information from various sources, or seeking help from your IT department. 

3 )Consistent quality data:

Data warehouses gather information from countless sources, but they convert it into a unified format to be used throughout your organization. What does this mean? Well, you can have confidence that each of your departments will be producing results which are in line and consistent with each other, which in turn ensures company-wide accuracy.

So, defining data warehouse characteristics is not as complicated or daunting as it may initially seem. In today’s increasingly connected world data warehouses are increasingly vital, because as data becomes more prevalent, its analysis becomes more and more crucial.

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Neville Kroeger

Neville Kroeger

Neville Kroeger is Product Marketing Manager at Automic Software, and has over 30 years’ industry experience. For the last 20 of these he has been designing and delivering workload automation solutions for enterprises of all sizes, around the world.