Traditionally, business intelligence (BI) has focused on areas such as supply chain or finances—niche subject areas poised to impact a handful of organizations.
Now, organizations in any industry have unprecedented opportunities to quickly make use of data for BI purposes.
Organizations that are able to turn data into insights and act upon them stand to gain huge competitive advantages. Several challenges exist when it comes to turning business data into actionable insights, but a modern analytics platform can overcome these obstacles.
Let’s dive into how your organization can use a modern data platform to generate valuable insights.
The many challenges of accessing data
Today, more than ever, you can look at much more data, much faster, and at a much cheaper rate. However, most data platforms are not set up to support rich data access or handle the volume of data organizations generate.
Consider a typical organization that is operating on-premises and building clusters. That organization needs a team of cluster administrators, plus a team of data scientists, who can mine the clusters for insight.
The system is the weakest link because they typically don’t scale efficiently. A far more flexible and responsive approach would be to drop a tool on top of a data lake and watch as actionable insights flow.
The pot committed fallacy prevents many organizations from recognizing where their current system is holding them back and investing in a modern platform. As such, companies like yours are more likely to continue using their current approach due to the technological and human capital invested in it, even when a modern platform could solve their pain points.
Another common data management challenge is elasticity. Companies using a historical data warehouse structure need to invest in extensive resources in order to accomplish small tasks. Since a modern data platform can scale when needs are high and shrink back as demand slows, it can be more cost-effective.
Turning data into actionable insights requires first and foremost that data be discoverable. Yet, many companies haven't made the necessary investments in cataloging data so it can be discovered.
Your organization can invest in the best resources for data ingestion and analysis, but if the data itself is not available for your stakeholders, you won’t realize a return on that investment.
How a modern data platform overcomes these challenges
To address the elasticity issue, modern data platforms are cloud native. A cloud-native approach is the best way to leverage elasticity to scale in a cost-effective way.
These platforms allow the data to be decoupled so one asset isn't dependent on something else. Decoupling data and data pipelines is a precedent to enhancing data discoverability. Any time the data is dependent on other pipelines, there's a loss of efficiency, as well as creating limitations on unique insights.
These represent a few of the most common challenges with turning data into actionable insight. Every organization has its own unique challenges and drivers for modernization. Any modern data platform should be tailored to the specific organizational drivers.
Understanding the current needs and goals is the first step toward modernization. Organizations also need to get the right team in place in-house and address a fear-based mentality of "if we do this, I will lose my job." Clearly understanding the evolution of roles can be a lubricant to that resistance.
Contact our team of experts to start migrating your data to the cloud today.
Keep up with Redapt
- Enterprise Infrastructure
- Data & Analytics
- Cloud Adoption
- Cloud Native
- Workplace Modernization
- Code Development
- Multi-Cloud Operations
- Google Cloud Platform (GCP)
- Security & Governance
- Tech We Like
- Dell EMC
- Managed Services
- IoT and Edge
- Business Transformation
- Microsoft Azure
- Emerging Tech