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When to Modernize Your Data Warehouse

Gaining a Competitive Advantage

Introduction

It’s no secret that data has become a mission-critical element for most organizations looking to grow their business. Without a solid data strategy, you are likely to fall behind or losing ground to your competitors quickly. Your data should be providing valuable insights into your business, and giving you the ability to be more efficient, productive, and, ultimately, more profitable. To enjoy these benefits, though, you need the right infrastructure that enables you to gather, store, and analyze your data efficiently. Yet, despite its importance and benefits, the decision on when to modernize your data warehouse can be a difficult one. So, whether you are with a large organization that has not had to go through a major data transformation in over a decade or a smaller company that wants to move to the cloud, there are some things you need to consider and challenges you need to be aware of.

But where do you start?

In this paper, we will examine this question in more detail and provide an overview of the challenges and when to consider modernizing your data warehouse based on your current needs and requirements.

 


 

PART ONE: WHAT IS A MODERN DATA WAREHOUSE?

Before looking at these challenges and why you need a modern data warehouse, it is important to understand what a modern data warehouse looks like. The first aspect is understanding how a modern data warehouse differs from a traditional data warehouse. 

There is no concrete definition of a modern data warehouse, but rather themes that occur in the modern data warehouse space. 

1. Moving to the Cloud

Of these themes, the first overriding, and most logical one is that modern data warehouses are almost exclusively moving to the cloud, irrespective of whether it is on Amazon, Google, Microsoft, or the database used. In contrast, most traditional warehouses were located on-premises. This meant all the data warehouse’s hardware and software infrastructure were installed and maintained on-site.

2. Data Refresh Rates

The next theme is the increasing shift to higher data refresh rates. Traditionally, organizations could manage when their data was refreshed overnight, or depending on the amount of data, weekly. Although not all organizations have the amount or type of data to justify faster refreshes, the trend is certainly that modern data warehouses implement more frequent intraday and even real-time refreshes.

3. Greater Number of Data Sources

Another common theme with modern data warehouses is the staggering number of data sources they should gather data from. Traditionally, data sources were relatively straightforward because organizations worked mostly with files and relational databases. Times have certainly moved in. Nowadays, organizations work with a variety of data sources that often contain various, disparate data types like CRMs, marketing platforms, email automation tools, business intelligence applications, and more, often all connected through a range of APIs. In fact, according to a recent survey, almost 20% of companies rely on twenty or more internal data sources alone.

4. Automation

In contrast to traditional data warehouses which required a fair number of manual processes, modern data warehouses have a high degree of automation. Now, this automation could take one or more various different forms. For example, it could automate:

  • Design
  • Development
  • Documentation
  • Deployment
  • Data Governance
  • CICD
  • Testing

Irrespective of what is automated, the trend is that automation is at the forefront of the modern data warehouse.

5. EMPHASIS ON DATA GOVERNANCE

With traditional data warehouses, data governance was almost an afterthought. It was a nice-to-have, and organizations would only consider it once everything else worked. With modern data warehouses, organizations are taking a completely different approach and implement data governance in the design of the data warehouse from the beginning. This is mainly due to two reasons. The first is that cybercrime is becoming an increasingly important consideration and people are now expecting and demanding that their data is safe. The second is that a variety of privacy laws and regulations now require proper data governance. Combined, people are, nowadays, more inclined to want to know what data an organization

Now that you have seen the overriding themes and identifying features of the modern data warehouse, let us look at why you need a modern data warehouse. 

PART TWO: WHY YOU NEED A MODERN DATA WAREHOUSE

Data has taken center stage for most modern organizations -- driving essential processes that organizations use to run their businesses effectively and productively. As a result, organizations are generating and using more data than ever before. This shift in day to day operations has many organizations scrambling for a better solution.

WTMYDW Computer

3. END USERS DEMANDS ARE INCREASING

End users also play a significant role in the need for a modern data warehouse. In simple terms, they are becoming increasingly sophisticated. As such, whereas they were satisfied with a dashboard and some reports in the past, now they expect and demand more functionality like integrated analytics, custom workflows, and no limits on data accessibility. Once again, traditional data warehouses struggle to deliver this.

1. More Data Use = More Complexity

Because of this, there is an increased need for more types of data analysis and an increased frequency of data analysis. This, in itself, brings about more complexity. This trend is also showing no signs of slowing down anytime soon, with the need for data analytics only expected to increase in the coming years.

2. Traditional Data Warehouses Can’t Keep Up

IT professionals and data engineering teams need to be able to adapt to more data and more types of data faster than ever before. This poses a significant challenge for teams still using traditional data warehouses, simply because the technology and hardware do not lend themselves well to scale and adapt as an organization’s needs and requirements change.

4. UPGRADING CAN SAVE MONEY

Another major challenge organizations face is cost. Let us face it, there is no getting away from the fact that on-premises infrastructure is expensive to implement and maintain. In contrast, the cost of cloud storage has dropped considerably in recent years and the cost of infrastructure for managing data centers is relatively cheap compared to physical hardware. So, for organizations whose existing data warehouses reach their end of life, their servers need to be updated, and their software licenses need to be renewed, this may present an opportunity to consider the implementation of a modern data warehouse.


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Data Pipeline

data pipelines: noun

  1. A Data Warehouse and the supporting processes and functions
  2. AKA Data Infrastructure

 

coffee table and laptop


Data Governance

Data Governance doesn’t need to be difficult to understand or implement. Yet according to a recent survey, 90% of executives do not trust their own data. Thousands of organizations will at some point struggle with fully recovering their data from a cyber attack. Establishing a successful Data Governance framework is crucial in order for organizations to increase data trust and bolster data security.

scientist


Data Science

data science: noun

  1. The process in which a scientific approach is applied to data to improve data, extract insights, reveal truths, and make better decisions.
  2. AKA Advanced Analytics, Predictive Analytics, Machine Learning & Artificial Intelligence

PART THREE: WHEN IS IT TIME TO IMPLEMENT A MODERN DATA WAREHOUSE?

The key to knowing when it is time to implement a modern data warehouse is by knowing where you are in the data maturity quadrant. Once you know this, you will be in the right position to judge whether modernizing your data warehouse is appropriate.

data maturity quadrant

 

1. HURT ZONE

At the bottom left of the quadrant, we have an area where organizations experience difficulty and challenges accessing their data and, as a result, they are not getting any value from their data. This is typically known as the hurt zone and is characterized by an organization’s inability to get to their data. 

Because of this, they are not effectively leveraging the data they have. As such, they are unable to analyze their data and gain valuable insights from it. This eliminates their ability to make data-driven decisions and the management of the organization is left to instinct and hunches. Fortunately, although this is not a good space to be in, not many organizations find themselves here. 

2. ACCESS ZONE

In the upper left corner of the quadrant, we find the access zone. In contrast to the hurt zone, organizations that find themselves here have access to their data. Unfortunately, the organizations here have not modernized their data warehouses with the result that, although they can access their data, they cannot get any value from it.

This will typically happen where organizations make data available to their users in some form like, for instance, Tableau, static reports, or even websites, but the users are not getting value from the data.

One of the main reasons why organizations find themselves here is that they have low engagement with their users. As a result, these users did not have much input into how the data is offered to them. The access zone typically also leads to a lot of questions in respect of the money spent on the data warehouse while it does not offer any value.

So, if you find yourself in the access zone, you will obviously want to move to a better place where you have access to your data and get value from it. To do this, you will need to up the engagement with your users and find an answer as to why they are not getting value from the data. Ultimately, this answer will guide you to a solution you can actually get value from.

3. DESPERATION ZONE

In a sense, the desperation zone is the converse of the access zone. In other words, organizations who find themselves here get a lot of value from their data, but they struggle to get access to their data.

What typically happens here is that organizations spend a lot of time and effort on gathering, assembling, and manipulating data. They will do this using a variety of desktop and business intelligence tools to get the right data and to gain insights from it. As a result, organizations in the desperation zone spend so much time trying to get the right data that they fail:

  • To make data-driven decisions
  • Let data drive the business and its processes.

Obviously, like the other zones, this is not a good place for any organization to find itself. What should happen instead is that these organizations should focus on running the business while using the right data solutions and data professionals ensure that they get the right data that enable them to do so. Ultimately, this will in most cases rely on systematic and automated approaches to improving the access to the data.

4. STRATEGIC ZONE 

Contrary to the zones mentioned above, the strategic zone is where most organizations want to be. When they are here, organizations have repeatable and reliable access to structured data. They also get value from their data. As a result, this allows these organizations and users to make data-driven decisions. 

So, simply put, these organizations have implemented a modern data warehousing solution. Now the question is whether they can improve if they already have access to their data and can derive value from it.

5. ELITE ZONE

Although it is not specifically on the quadrant, organizations that find themselves here have secure data with proper data governance strategies and tools in place. They also have all the data necessary to ensure the efficient running of the business and its process, but they are also capable of adding data sources at the speed at which the organization requires it. 

Considering the above, this is the space where all organizations should aspire to be. This does not happen overnight, though, and organizations should first reach the strategic zone before considering implementing the necessary solutions to move the elite zone. 

What may be helpful is to think of the quadrant and rate yourself between 1 and 10 to see where you fall on the quadrant. So, you should consider how your business users feel about their access to the data. Also, you need to consider what value you are getting from the data. 

WTMYDW Lady

 

Based on this, you will then be able to see what zone you are in and where you want to go to. In this way, you will determine what is necessary to move to the strategic zone and beyond to the elite zone. 

The Bottom Line

In a world where data is becoming increasingly important to ensure the efficient and productive running of a business, it is vital that you know where you are in respect of your data warehouse solution. 

If you are in the Hurt, Access, or Desperation zones described above, you should start planning your data transformation to ensure that you get to the Strategic zone, and, in the longer term, to the Elite zone. It is the only place where you will get full access to your data and get the full value from it. 

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