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5 Things You Should Know About Modern Data Stack


Bash Sarmiento

Modernization prompts a lot of aspects of our life to be digitized. It goes the same for the data we use in our everyday lives — especially at work. As more industries migrate their company data in cloud storage, the term modern data stack becomes more prominent. But what do we mean by this?

A modern data stack can sound overwhelming. However, it simply describes the different tools that make a data’s life cycle run appropriately based on its purpose. It’s a stack of industry-specific tools that completes the different phases of data organization. Think of it as the process of segregating your files in a computer before modifying it depending on desired outputs or work requirements. Data stacks are built to support the storage and accessibility of a company’s data.

Still a little confused? Here is a list of things you should know about modern data stacks that could help improve your organization’s workflow and increase productivity within your company.

1. Modern data stack depends on the new technologies for each data phase.

Digital data undergoes so much processing, and like a living organism, it has its lifecycle. To fully grasp the entirety of the modern data stack, dividing its life cycle into phases can be beneficial to avoid overlap in stacking technologies together.

To give you an overview of a data life cycle, here are sample domains of data processing in terms of analytics:

  1. Data Extraction – Producing the actual data based on schools of thought and raw ideas.
  2. Data Ingestion - Data is uploaded or exported in a safe yet convenient centralized location.
  3. Data Storage – Safeguarding data in an encrypted location that can be accessed only by select people for analysis.
  4. Data Integration – Maximizing mileages of data by expounding its results to more outputs and materials.
  5. Data Transformation – Utilizing given data to execute campaigns or create new ones building on these ideas.
  6. Data Cleansing – Stripping data on the issues that risks the value of stacked information.
  7. Data Validation – Data presented is collected accurately with the right tools.
  8. Data Presentation – Tailor-fitting data to produce video material, marketing or content campaign, or email blasts to your target audience.

This data lifecycle has been used and redefined through every industry. There’s nothing new about it. However, technology continues to evolve every day, and it makes up for the modernity of the data stack that organizations and data analysts utilize for this work process.

2. Invest in how you can make the most out of your stacked data.

Instead of migrating into different cloud systems for each phase of the data cycle, invest your money and time on a fully managed cloud database. By doing this, you’re eliminating a lot of layers in data processing–specifically, administration. This process can further increase the company's productivity with your stacked data producing valuable information to make data-driven decisions. You can also save a considerable amount of time and money through modern stack data.

3. Modern data stacking allows real-time results and analytics.

Of course, there is a corresponding data organization process suitable for various business models. For workplaces that require fast-paced development of data life cycles, modern data transformation processes move organizations to produce real-time analytics with reliable results.

4. Cloud storage is essential to modern data stacks.

Cloud storage is a tool that ensures the security, flexibility, and accessibility of your company's data. This is a cost-effective way to store and organize large amounts of data. And since it is easily accessible, the cloud makes processing faster within minutes than before when it took manual extraction due to limited processing capabilities.

5. Data stacking democratizes data exploration.

Back then, it took days and even weeks for data analysts to pull a piece of certain information that an executive needs. However, as things become more digitized, handling data shifted into a much-democratized process. Databases, nowadays, are now accessible for more employees in the workplace. This prevented more bottlenecks to the business process of a company. Since everyone is empowered to utilize and explore the data available, strategy managers and sales executives can access relevant information to apply to their digital campaigns without relying on analysts.

What’s next?: Implementing Modern Data Stack in Your Business

Modern data stack has a lot of upsides in streamlining your business and stepping up the productivity game in the workplace. You just have to find the appropriate tools and techniques that suit your business model.

Evaluate work processes. To get started, perform assessment tests on your workflow and evaluate which parts of a data lifecycle you must improve. Typically, data extraction and ingestion are the most common bottlenecks of companies. So, make sure to identify the right phases to work on to avoid the overlap of tools and redundancy of its functions.

Think about your team. Consider your employees and how quickly they can adapt to this change. What are their needs in terms of transforming these data into decisions and campaigns? What would help them the most in implementing your business goals?

Look into flexibility. Ask yourself, "do your stacking tools and technologies have the elasticity to adapt to the workflow of your organization?". These tools should make data processing more seamless for you, not the other way around. If it does, consider going back to step one and reassessing what your company needs.

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