The demand for access to actionable data has never been higher. The challenge for data professionals lies in meeting this demand while ensuring that:
- Access to data is managed in a secure, governed, and scalable way.
- Adoption of data tools and technology occurs.
To delve into this, we hosted a recent meetup in Barcelona, a thriving hub for data-driven organizations. We brought together some of the brightest regional minds in data from CIS Consulting, Looker, Snowflake, Fivetran, King, Marfeel, and more. Here are the core themes we observed:
Three key considerations for your data tech stack
Traditional data infrastructures have evolved significantly. The increase in cloud-based solutions has given organizations unlimited and uninhibited capabilities to store, process, and analyze their ever-growing databases.
Because of this, companies can now tap their data’s real potential with the help of new and reimagined data solutions.
There is a new approach to ingesting data from multiple sources which involves extracting, loading, and then transforming data (ELT approach) as opposed to traditional ETL.
This new blueprint for data integration tools (which leaves the transformation stage until last) allows engineers to create a more flexible stack. With it, they can easily apply changes to the business model at a later stage — saving time and money.
Data storage, like data integration, has also evolved. Modern tech stacks need a database solution that can support organizations as they scale, handling increasing volumes of data without compromising on reliability or performance.
Security and data protection must exist in every aspect of a cloud warehouse architecture. Whereas warehousing used to be complex and inflexible, newer cloud-based databases have turned the industry on its head.
By separating storage from computing, both data providers and consumers are now able to share live data concurrently in a secure and managed environment.
Today’s data analytics platforms need to fit into the workflow of the entire company and provide a single version of the truth. By doing this, organizations enable their business users to carry out the analytics they require on a daily basis.
This approach to analytics, where quality information is easily accessed, means that high-functioning and efficient teams can make critical data-based decisions.
Cost saving and growth aiding
Most businesses are actively looking for ways to reduce unnecessary costs and drive growth. Understanding the new data technologies available can be the key to a data-driven strategy. This strategy enables lowered operational costs, improved profit margins, and — ultimately — a competitive advantage in the market.
King, the mobile gaming giants that brought Candy Crush to the world, implemented an incident management process that allowed them to reduce the operational cost of incidents by 70%. They highlighted how Looker has been pivotal in the process by providing the ability to run root cause analysis and anomaly detection on vast amounts of data.
In general, there is a significant inefficiency in IT staff and analysts spending endless hours on laborious and time-consuming “data cleansing” tasks.
Implementing a data stack that removes the complexities of data preparation and transformation allows these teams to focus their efforts on creating real value for the enterprise and data consumers.
This reallocation of brainpower to focus on data-driven strategy is often the key to driving creativity and unlocking new market potential.
In the end, it’s about culture
Organizations are focused on creating and embracing a data-driven culture as a part of their core data initiatives. Driving adoption is the key to unlocking true business value from a data stack.
For adoption to happen, the value of technology must be communicated and shared across the company. Utilizing a data stack with agile technologies that grows with the company, inspires new ideas, and unifies all business departments makes this value obvious. Once a culture achieves data appreciation — and there is a desire to shift the culture to revolve around data — being “data-driven” can go beyond theoretical.
When guided by the use of the right technologies, it can become one of the operational foundations of the company.