5 Strategies How Modern Data Stack Can Improve Your Analytics

Modern businesses of all sizes are always looking to harness company data to maximize their growth and optimize sales. One of the most powerful processes that ensure data-driven decision-making is data analytics for business.


Modern data stack offers a cost-efficient solution that allows near-infinite manageability to generate analytics from company data. The entire process can be daunting, but there are strategies to simplify the whole process. Here are 5 strategies that can help your modern data stack improve your analytics.


What is a Modern Data Stack?

Before we go building analytics strategies, we need to understand what a modern data stack is. To simplify, a modern data stack is a combination of different tools on the cloud that organizations use for data integration. The goal of the MDS is to analyse your business data in the hopes of unravelling areas of business opportunity and maximizing efficiency.


What separates them from legacy data stacks is their position in the cloud. As MDS is in the cloud, IT teams didn’t need to create their own technical configurations. Beyond giving away direct access to hackers, there’s very little chance for data breach too.


A modern data stack will have, at least, an extract, load, and transform (ELT) data pipeline for data lake implementations. It will also have a data lake destination or a columnar warehouse in the cloud, together with data transformation and business intelligence tools.


MDS lowers the technical barrier of entry for companies that need advanced data integration. Many MDS components are directed towards businesses that need analytics. It allows users from all backgrounds without the need for more technical knowledge. So, what strategies can you use with MDS to improve your analytics?


  1. Start With The Right Data Sources

A modern data stack architecture can only generate analytics with the right data sources in mind. Sure, traditional data warehouses still exist, especially for businesses that need to follow specific laws like HIPAA compliance and SOC2. Then again, there are better choices beyond OLTP data systems.


If you plan to maximize an MDS, expect features and components to contain the bells and whistles you need and add more as needed. Pay-as-you-go data stacks allow for better utilization of features, charging you only for what you use.


Features like built-in compression, concurrency, performance, and security change depending on the needs of your business. With your modern data stack, you want to be up and running as soon as possible. You want uncomplicated licensing that will provide everything you need to parse your analytics data.


  1. Assess the Existing Landscape and Build Expertise

The most critical strategy to the modern data stack is assessing the existing landscape for your business. Many companies’ growth relies on better utilization of company data. Companies want to turn planning and decision-making into a repeatable science rather than an art.


With that said, you want to ensure that you have a team that maximizes growth and efficiency rather than have third-party vendors come in and tell you how a modern data stack works on the surface level. Sure, everything will stay humming and pristine for a bit, but once you need to move to something better, the in-depth knowledge should be your team.


Sure, MDS is more end-user friendly than traditional data warehouses but hiring experts or building your own knowledge base is a vital strategy to extract more analytics you need without the middleman.


  1. Build Towards Actionable Business Intelligence And Workflow Loops

Analytics is derived mainly through business intelligence tools, and it has become the truth and reality for businesses who want data-driven decisions. BI itself is an evolving process, and with it, you want actionable business intelligence. This helps users make positive changes as they develop the business.


Decisions that use actionable business intelligence give you two advantages: they are autonomous in nature and help predict its next viable move. Businesses also use BI to improve their workflow and create a closed-loop between data and operational pipelines.


It’s crucial to merge business intelligence into your workflows to create a customizable BI platform. Doing so will improve the analytics you need because you automate the feedback loop through the data generated.


When using business intelligence loops into your workflow, expect improvements in many areas of your business. The delivery of products, services, and solutions, in particular, will see remarkable progress due to the level of agility to build for the company.


  1. Invest in More Cloud and Multi-Cloud Solutions

Nowadays, businesses don’t have the funding or motivation to invest in on-site data centres. Instead, several industries are moving to the cloud and multi-cloud solutions, especially for generating analytics data. As modern data stacks mostly live on the cloud, the shift is almost a must if you want to be competitive.


If you’re a business looking to utilize the capabilities of MDS, you need to understand the power of the cloud and its capacity and accessibility. You want to embrace cloud solutions to create a more digital environment that does not rely on traditional data lakes and data centres.


Follow existing modern data stack trends and keep investing in cloud solutions. They are highly secure, private, and have strong data governance capabilities. Depending on your industry, business size, or location, you can rely on them, so moving much of your business to the cloud can simplify your analytics processing.


  1. Explore AI and Machine Learning Trends

With the modern data stack comes artificial intelligence and machine learning, which will play a crucial role in business analytics. AI/ML-driven intelligence can help improve and evolve your analytics to the next level, and you need to know when to leverage them.


Modern data stack trends point towards using historical and real-time data, combining them to execute digital functions in analytics and get better autonomy. Both data types can evolve data analysis towards more accurate and actionable insights.


Artificial intelligence and machine learning can do a lot of great things. You want to harness both technologies and integrate them into your natural business workflow as it evolves. This will generate more data that will accurately build on your data assets and assess what you need to grow.


Final Thoughts

Using modern data stack to improve your analytics does not simply mean you input data and see what it spits out. You want to leverage your cloud capabilities, invest in them, and integrate them within your workflows to understand better how you do business.


Make the best use of the strategies we listed above, and you’ll surely get more out of your MDS and your analytics in general. Whether you’re a startup, a small business, or a big corporation, these tips can help you get ahead.