What’s a Data Platform?

A data platform is a complete solution for ingesting, processing, analyzing, and presenting the data that systems, processes, and infrastructures generate in a modern organization.

While a business can utilize several purpose-specific applications to manage each aspect of the data puzzle, a complete data platform can provide well-rounded data management solutions.

The right data platform manages more types and structures of data across the organization. In other words, a data platform should handle all data your business ingests or generate.

An excellent modern data platform must contain the following layers:

1. Data Integration

Data integrationis the practice of consolidating data from different sources into a single data set to help you get a complete view of the business. The purpose of data integration is to achieve the following:

• Get a collective view of business data for efficient data management
• Derive meaningful insight from the organization’s data
• Gain actionable intelligence from business data

With the tremendous growth of data volume, data coming in different formats, and the need to distribute data more than ever, your data platform should aim at aggregating data regardless of the type, volume, or structure.

Data integration is a critical part of the data pipeline because it determines other phases such as:

• Data ingestion
• Data storage
• Data processing
• Data transformation

Data integration ensures you don’t have conflicting data versions, outdated data, or lost sheets. Instead, you’ll have a single source of truth for everyone.

2. Data Management

After integrating all the data your company generates or ingests, your data platform should allow you to manage the data. The platform should be able to do all the processing you need to make data actionable, such as:

• Data transformation: The process entails converting data from one format to another to make it more valuable. Data transformation can involve converting raw data into a clean useable form, converting data types, removing duplicates, and enriching data to benefit your organization. Your data platform should be able to extract data from a source, convert it into a clean format that you can use, and then deliver it to a specific location.
• Data modeling: The process includes creating a visual representation of the whole information system or part of it to communicate connections between data points and structures. You can think of data models as flowcharts illustrating data entities and how the entities relate. Your data platform should allow data modeling.
• Data clean-up: Data cleaning involves removing unwanted data, unifying data structures from different sources, standardizing your data, fixing cross-set data errors, dealing with missing data, and validating your data. A platform that allows you to execute data clean-up would be invaluable.
• Data Enrichment: Enriching data is the process of enhancing the data you collected with the relevant context you obtained from additional sources. Enriched data is a valuable asset because it’s more insightful and useful.

You should go for a data platform that allows data enrichment on raw data.

3. Data Analytics (Business Intelligence)

Data analytics is the process of examining data sets to find trends, draw conclusions, and find meaningful insights. Organizations use insights from data analytics to inform and drive smart business decisions.

Your data platform should allow you to extract raw data, organize it, and then analyze it. That way, you can transform the data from incomprehensible numbers into coherent, intelligible information.

The information from data analytics is critical for developing suggestions and recommendations about your company’s next steps. Data analytics create your business intelligence.

4. Data Visualization

Data visualization is the graphical representation of information. Visualization will transform data into charts, tables, graphs, and maps to help you convey information quickly.

Visualizing data allows people to access and understand your data’s patterns, trends, and outliers. In the world of big data, you need a data platform that lets you make sense of millions of rows of data you generate daily.

A data platform that allows data visualization can help a business achieve the following:

• Establish business trends, patterns, and insights
• Compare and contrast metrics easily
• Absorb a large amount of data at scale
• Identify questions that a business would otherwise miss
• Simplify reporting

5. Data Sharing

Data sharing is the distribution of the same sets of data resources or dashboard reports with many users or applications without interfering with data integrity across all the systems.

Data sharing is critical for businesses of any size because organizations want to share insights with employees and other stakeholders for a more business intelligence process.

From the dashboard, you can create a link to share with:

• Employees
• Partners
• Customers
• Board members

A link that allows you to share data and collaborate with others seamlessly.

How to Choose a Data Platform That Drives Business Intelligence

Unfortunately, picking the right data platform to keep your business on the right path is challenging. After all, every business has different data platform needs.

Bigger companies are more likely to build custom data platform solutions or invest in separate tools to match their desired capabilities. On the other hand, small and medium-sized businesses can go for a full-stack platform.

Whichever option your company goes for, there are some features you must consider, but we want to focus on the four most important ones.

1. Functionalities

While we’ve listed several functionalities that a modern platform must-have, your company has the task of deciding what’s important. Behind the same expression can lie different realities.

A great example is the intuitive data visualization feature. What might be intuitive for one might not be the best for everyone. Your best shot is to try them yourself.

You should examine the functionalities of the data platform you’re considering and check if it can help you unlock the true value of your data. The features must help your business manage day-to-day operations, shape your long-term strategy, and deliver measurable ROI.

2. Professional Services and Support

When choosing a data platform, you should establish what you want from the service provider. Some platforms base their services on being helpful and while other data platforms like open-source solutions and self-hosted platforms are more self-guided. When you choose such solutions, you buy from the vendor and will depend on the following for support:

1. Internal expertise
2. FAQs
3. How-to documented guides on how to get the most out of the platform
4. Third-party vendors

3. Support

You should consider the type of support the vendor offers. The vendor might be offering support through different communication channels, such as live chat, phone, or email. Ensure you’re okay with how the provider channel support

More importantly, confirm if the provider will help you with onboarding, provide technical support when you get stuck, reach back in real-time, and answer your questions when you need clarity.

4. Cost Structure

Many things influence the price of a data platform, such as:

• Going for 100% cloud data platform or not.
• Choosing a self-analytic platform or going for an option that requires you to pay a consultant to help you get started with the data platform
• When the data platform is cloud and self-service — you might need training, or you’d want professional service to help you if you’re completely new in the data analytics world
• Data connectors — check if the subscription you’re going for includes all the connectors your business want

Other considerations that affect what you’ll pay for a data platform include data refreshes and storage. You should check everything to ensure what matters most to your business are not hyper-expensive.