The Ultimate Guide to Data Warehouse Automation and Tools

insightsoftware -
April 19, 2021

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Executives increasingly rely on data and advanced analytics to make business decisions. They also need the ability to access and parse that data faster and in more creative ways. Meanwhile, the data that businesses have access to and the number of systems producing that data are growing at lightspeed. This puts tremendous stress on the teams managing data warehouses, and they struggle to keep up with the demand for increasingly advanced analytic requests.

To gather and clean data from all internal systems and gain the business insights needed to make smarter decisions, businesses need to invest in data warehouse automation.

What is Data Warehouse Automation?

Data warehouse automation refers to the process of automating each part of the data warehouse lifecycle by minimizing manual code writing and automating the repetitive, labor-intensive, time-consuming tasks normally associated with a data warehouse. These tasks include up-front analysis, design, and modeling. Essentially, data warehouse automation allows businesses to quickly collect, clean, and prepare data for analysis without requiring engineers to write any code.

Taking a step back, data warehouses provide value to organizations because they provide a single source of truth for an organization’s internal and external data. Business Intelligence (BI) and IT teams can pull customer, product, and market data from disparate systems, then clean and prepare it for analysis so executives can make more informed decisions.

Traditional data warehousing methodology, however, has long frustrated both tech and leadership teams because the process of executing a BI project tends to be long, tiring, and expensive. In fact, the average data warehouse implementation takes 17 months. By the time you complete the project, the data needed by leadership are no longer relevant. But with data warehouse automation, an initial BI implementation can be up to five times faster than traditional methods, which results in a higher success rate for BI projects.

More importantly, data warehouse automation provides more accurate data, creates operational efficiencies, offers solutions to compliance issues, and delivers business insights faster. In short, it’s more or less a necessity for businesses that hope to stay competitive in an increasingly fast-paced and data-driven world.

The Growing Demand for Data Warehouse Automation

Though data warehouse automation has been around for more than a decade, the demand for it among business intelligence teams, IT departments, and corporate management is increasing.

According to a global survey on the status of data warehouse modernization from the Business Application Research Center, the most pressing issue for 44 percent of survey participants is a lack of agility in the data warehouse development process.

This is the exact problem data warehouse automation solves. As businesses undergo digital transformations and adopt products that automate various processes across the organization, executives need to add a data warehouse automation solution to the top of the list of products that will modernize the business.

The Benefits of Data Warehouse Automation

There are several advantages of incorporating data warehouse automation into businesses of all sizes in nearly every industry. Automation benefits teams across the organization from IT to the C-suite. Though there is no shortage of ways automation can improve operations, these are the five most important benefits of data warehouse automation.

  1. Reclaim Developer Hours

Whether a business is building a new data warehouse and set of OLAP cubes or revamping an existing one, the project requires developers to write a massive amount of SQL code. The process of writing and testing this code is extremely time time-consuming, labor-intensive, and error-prone. In some cases, it might take even the most skilled SQL programmer hours to move a single field from a source database to a target destination.

But a data warehouse automation platform is like a code-generating machine, writing a substantial amount of code in the background. It uses the same underlying tools and processes as if a developer coded the process manually, but it takes seconds to complete the operation instead of hours of manual coding. Developers can extract data from various data sources, then specify a set of rules to transform the data in a simple drag-and-drop interface that automates all the SQL code automatically. They can even add new data sources on the fly with the click of a mouse.

This significantly reduces the number of developer hours needed to build a data warehouse or perform BI tasks, which results in leaner operations and more time for developers to focus on other projects.

The same holds true for organizations that depend on external specialists to create and manage SQL scripts and maintain their data warehouse. A data warehouse automation platform can result in significant savings for those organizations as well, as the cost of external specialist hours can quickly mount up otherwise.

  1. Get More Accurate Data

Data is messy. Any large data set is guaranteed to have gaps, errors, and duplications. You need to discover, understand and rectify these issues before you use the data. This exercise is often time-consuming because developers and BI teams need to combine several data sets to get a full view of company operations and make sense of the data.

In a typical multi-database scenario, getting the data from multiple source systems to match requires a mapping exercise. Using traditional methods, developers write and maintain SQL code to handle this mapping. This is a great example of a time-consuming, repetitive task that doesn’t require human creativity and is better accomplished through automation. Data warehouse automation software accomplishes this task with the click of a mouse and frees up developers to focus on more complex tasks.

Not only does data warehouse automation software perform mapping exercises that rectify data discrepancies, but it eliminates the human error that comes with copying and pasting data and manually writing code. With more accurate data, companies save time and money, and business intelligence teams can deliver more accurate results faster.

  1. Free up Developers to Work on Strategy

When developers aren’t wasting time on repetitive coding tasks, they are free to work on more important and valuable projects. According to The Data Warehousing Institute (TDWI), a think tank devoted to all things data (and a great resource for education and training), data automation liberates IT from spending significant time on mundane tasks, allowing them to focus on more strategic, game-changing breakthroughs for the enterprise.

These developers can work on tools, processes, and strategies that enhance the productivity of your organization rather than coding a database that might prove to be obsolete by the time they’re finished with it.

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  1. Gather More Valuable Business Insights

The same survey that found the most pressing issue for 44 percent of participants to be a lack of agility in the data warehouse development process also reported that 42 percent of respondents said a benefit of data warehouse automation is the enablement of self-service business insights.

With the implementation of data warehouse automation comes a mindset shift from “get it right the first time” to “develop fast and frequently.” In order to deliver a BI product that businesspeople will actually use, organizations first must develop a shared vision and understanding of the data points and numbers that will tell a valuable story of the organization and how well it’s operating. Getting all stakeholders to agree on those data points or even the story they’re trying to tell can be difficult.

A data warehouse automation platform, however, can help by delivering results rapidly and easily. Data warehouse automation offers organizations the agility to quickly combine disparate pieces of data, take them through a complete BI development cycle, and deliver the result to the business to see whether a given set of parameters yields valuable insights. If a clear story doesn’t appear, they can go back to the drawing board and pull a new combination of data points until a story emerges.

This exercise would be unthinkable using the traditional data warehouse model because it would take weeks, if not months, to do. With data warehouse automation, you can complete this in hours. It essentially allows businesses to fail fast in their testing.

This is perhaps the most intriguing promise of data warehouse automation: it is a technology that solves long-standing problems and has a ripple effect on non-technology issues. Business users get what they want, when they want it, rather than six months later. You can consistently realize rapid time-to-value since new BI and analytic functionality can be delivered in days instead of months.

  1. Maintain Compliance

Privacy and the security of customer data are hot topics that are constantly appearing in the news, so it’s essential for businesses to operate in a way that meets requirements for regulatory compliance and protects customer data. According to TDWI, automated data warehousing “can better assist you in maintaining governance and compliance by automatically documenting your data.” You can automatically track and document every process, so there’s transparency as to how you use data and where it’s stored. Here, too, the automated processes allow less room for human error that might corrupt or compromise a company’s data.

Because data warehousing automation tools allow you to generate documentation automatically, they can assist an organization with tracking how data flows for GDPR purposes. If scripts are written manually, there is often poor documentation and the knowledge about what the scripts do and how they work is retained by the individual developers. That can cause obvious challenges when staff leave an organization. Using automation tools standardizes the process and enables multiple people to contribute to a project, seamlessly picking up where others left off and helping keep documentation on track and compliant.

How to Automate Your Data Warehouse

BI projects like building a data warehouse or transitioning to a more modern infrastructure don’t need to be complicated and frustrating, nor do they need to take years and thousands of developer hours to complete. Businesses can save time, money, and frustration, all while getting more accurate data and better business insights with data warehouse automation software.

insightsoftware firmly believes that data warehouse automation can bring tremendous value to IT groups and business users alike. Jet Analytics, our data warehouse automation software, is easy to install, intuitive, and seamlessly integrates with Microsoft Dynamics.

Whether you have an existing data warehouse that could benefit from automation or you’re starting from scratch, the experts at insightsoftware can help. Learn more about Jet Analytics and request a free demo today.

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