It’s Time to Modernize Your Data Analytics Stack

We recently worked with a leading national commercial bank specializing in commercial and consumer mortgage loans. The bank held a wealth of valuable information that was locked up in transactional data. The decision to utilize the data immediately led to more personalized campaigns.

We helped the bank design and implement a modern data stack that enabled them to unlock the potential of the mountains of data they were sitting on. The bank was able to better segment their client base, create personas and make their messaging more likely to resonate. Additionally, they were able to track campaign results and make adjustments in real-time to ensure that they were meeting their targets. The use of data and analytics was key to the success of the campaign.

Today, the term “modern data stack” is ubiquitous. It is used to describe a set of data management tools that work together to provide a complete solution for managing data. The stack usually includes a data warehouse, a data lake, and a data management platform. These tools work together to provide a complete solution, from ingestion and storage to analysis and decision-making.

The origins of the modern data stack likely date back to the original large BI platforms, such as Microstrategy and Business Objects, and columnar cloud databases such as Redshift. Since then, the stack has continued to evolve into a complex and ever changing ecosystem of tools, techniques and best practices.

The richness of this ecosystem provides numerous options for varied architectures, but it also introduces complexity that can make it difficult to find viable, flexible solutions that target a range of business problems and continue to provide business value for years to come.

Key Considerations for a Modern Data Stack

There are a few key factors to consider before deciding to implement a modern data stack. First, consider the size and complexity of your data. If you have a large amount of data or if your data is complex and difficult to manage, a modern data stack may be just what you need. Second, consider your business needs. If you need to be able to quickly and easily access your data, analyze it, and make decisions based on it, a modern data stack can provide the agility and the tools to get your data into the right hands.

Ultimately, you will have to also consider cost and resource availability, but you can always decide to introduce features through a phased approach, introducing cumulative efficiencies and reaping benefits at every stage of the implementation. But, taking that first step is critical.

Tools of the Modern Data Stack

When implementing a modern data stack, it’s important to choose the right tools for your business and the solution you’re trying to solve. There are a number of platforms and tools on the market, so it’s crucial to find the best combination that fits your needs. Additionally, you must organize and store your data properly. A data warehouse or data lake can provide a great place to store your data, but you need to make sure that it’s properly organized and accessible. Finally, you need to ensure that your data platform is kept secure, that sensitive data containing PII are secured and that your data conforms to data protection regulations.

The Benefits of A Modern Data Stack

Not Just a Technical Solution

Organizations that leverage a modern analytics stack can streamline operations and minimize cost, but that is only the start. From there, an organization can also begin to address its larger objectives, innovating its product lifecycle and creating a distinctive value proposition that will likely delight their customers. Data is at the heart of all of these activities and how it is collected, harnessed and applied to a host of business activities can make all the difference.

The modern data stack has also become the central tenant for achieving a competitive advantage in data-driven organizations. Organizations that leverage analytics are able to improve customer satisfaction levels by identifying what matters most to their customers and then providing tailored or even personalized products and services. This allows them to create a better customer experience and improve customer retention rates.

In order to effectively compete in fast-moving, highly-competitive markets, organizations need to offer products and services that are highly valued by their customers. And, to continue to retain a competitive advantage, organizations need to constantly innovate to find new ways to meet their customers’ evolving needs. Concurrently, organizations need to be able to effectively communicate with their customers to reinforce through their messaging key differentiators that set their products and services apart from their competitor’s offerings.

An organization’s capacity to consistently execute effectively at these levels can only be achieved when an organization embraces a data-driven culture and makes data collection and analysis its core competency. Reacting to market events or a competitor’s recent innovation will likely end up being a costly mistake and a lost opportunity. So, unless an organization is leveraging its data to innovate and stay in touch with their customers, they will invariably fall behind their more agile competitors.

The benefits of implementing a modern data stack are numerous and can lead improved operational efficiencies, reductions in cost, mitigated risks and increased revenues.

A partial list includes:

1. Improved decision-making
   Organizations that use analytics are able to make better and more timely decisions as they have access to a large amount of relevant data that can help identify patterns and trends. With an analytic capability, an organization can make informed decisions based on data and facts instead of unverified intuition.
2. Increased efficiency
   Analytics can help organizations streamline operations and processes, which can lead to increased productivity and efficiency.
3. Increased revenues
   Organizations with a deep analytic capacity can leverage their capabilities to directly impact their revenues streams as they are able to quickly identify new opportunities and move into new markets.
4. Reduced risks
   An analytics capacity can help organizations identify and mitigate risks, avoiding potential losses.
5. Improved customer satisfaction

A strong analytics capability is essential for any organization that wants to be successful in today’s competitive landscape. Analytics allows organizations to make better decisions, optimize their operations, and gain a competitive advantage.