×

Scuba Tech Library

What is a Data Platform?

As the sheer volume of recorded human data continues to explode from 4.4 zettabytes in 2013 to 44 zettabytes in 2020, now more than ever, companies are utilizing data platforms to synthesize this overwhelming deluge of information. Whether it’s Amazon congregating user data to predict market conditions, or Oracle pinpointing the weak links in a supply chain, data platforms are how today’s market leaders stay competitive.

Data platforms are software technologies that allow businesses to collect, analyze, and present data. These invaluable tools can be used for a variety of uses, including congregating data across various divisions within a company, sharing metadata to other users, or running recommendation engines.

Different kinds of data platforms

Data platforms fall within specific categorizations, though most incorporate multiple elements. The different kinds of platforms are:

  • Enterprise data platforms are central data repositories that consolidate information across all facets of an organization, including customer service and marketing. This is the foundation of all operational and enhanced data functions.
  • Modern data platforms provide an adaptable architecture of future data analytics. This avoids the common pitfalls of antiquated data lakes by quickly adopting new technologies and optimizing hardware usage.
  • Cloud data platforms are built entirely from cloud computing and data stores. This allows for easier data access and scalability.
  • Data analytics platforms perform analyses across an organization’s various data systems. These turn any and all data collected into actionable business insights.
  • Consumer data platforms create unified consumer databases. These consolidate user data into easily accessible user profiles that can be shared with other systems within an organization.

Benefits of Data Platforms

Data platforms are necessary tools for competitive companies to stay organized, informed, and protected. Some benefits include:

  • Security: Data platforms give organizations control over what data is accessible and who has access to them.
  • Centralization: A good data platform supports all types of sources, such as MySQL, Cassandra, or monteDB.
  • Governance: Data platforms streamline adherence to ever-changing regulatory requirements, thus reducing operational costs and remaining compliant with industry standards.
  • Delivery: Data platforms that allow and enable key functions, such as scheduling and proactive alerts are paramount.
  • Availability: Data platforms should be easily accessible by its user, including high-end point users like data analysts and scientists.

Get real-time data analytics with Scuba

Though there are many different kinds of data platforms, Scuba’s continuous intelligence platform offers unmatched security, data centralization, governance accessibility, delivery, and availability. Scuba offers elevated data management and analytics in real-time, and is designed to be accessible to users across your organization. 

Request a demo or reach out to a Scuba expert today.

Related

Data Science

Data Lakes and Data Warehouses -- Which Is Right For You?

Data lakes and data warehouses are both commonly used for storing data, but there are key differences between the two that make them unique in their own way. Learn which fits your business purposes best and if there is a better solution.

Data Science

What is a Data Ecosystem?

The term “data ecosystem” collectively refers to all the programming languages, algorithms, applications, and the general infrastructure used to collect, analyze and store data.

Data Science

What is Data Modeling

Data modeling is a means of creating a conceptual framework for your data in preparation for storage in a data warehouse. The resulting model is a visual representation of the data which maps out the relationships between data, and the rules.

Data Science

What is Lambda Architecture?

Lambda architecture processes data through a hybrid combination of batch processing and stream processing.

Data Science

What is an ETL Pipeline?

ETL is a method to collect raw data from various sources, clean it up, and translate it so it can be used to inform decision making.

Data Science

What is Data Governance?

Data governance allows organizations to ensure high-quality data through formalized processes for management, monitoring, and control of data assets.

Data Science

What is Hadoop?

Apache Hadoop is one of the most widely used open source frameworks designed to address the problem of storing and processing big data.

Data Science

What is Parquet?

Unlike row-based formats such as CSV, Parquet is a columnar data file storage format.

Data Science

What is Querying?

A query is a question or request for a database written in a code the database can understand, in order to retrieve or modify the correct information.

Data Science

What is an Ad Hoc Query?

An ad hoc query is any kind of question you can ask a data system off the top of your head.

Data Science

What is Metadata Storage?

When building a database, all data requires some description to help identify its uniqueness, which is where metadata comes in.

Data Science

What is an Enterprise Data Warehouse?

An EDW is a database that centralizes data from across the business so it can be analyzed and used in decision making.

Data Science

What is Time-Series Data?

Time-series data analysis serves critical functions in most modern industries, and is a powerful method to glean accurate analysis.

Data Science

What is Data Sovereignty?

Data sovereignty defines the regulations data is subject to. Fortunately, there are actionable steps brands can take to ensure compliance.

Data Science

What is Self-Service Analytics?

Self-service analytics empower non-technical teams to interact with data, perform queries, and glean helpful business insights.

From Our Blog

See All
two men celebrating with smart phones thumbnail

Mastering the DX 2.0 Economy: How Customer Intelligence Helps Media & Ad Tech Brands Thrive

As AI, IoT, and data privacy regulations continue to evolve, there is tremendous potential for consumer-focused industries to transform the way they interact with customers. In a privacy-first DX 2.0 economy, a brand's success depends on its ability to quickly generate comprehensive 360° customer profiles, analyze data from multiple channels, and deliver dynamic and hyper-personalized experiences in real-time.

Learn More
data systems thumbnail

4 Game-Changing Benefits of a Privacy-Centric Single-Stack Analytics Solution

The future of privacy compliance is still in limbo, but one to keep tabs on. President Biden’s recent executive order may have laid the framework for a new era of transatlantic privacy compliance, but it will likely be several months before the framework receives EU regulator approval, let alone the enviable legal challenges to follow. In the meantime, the stakes have never been higher for transatlantic brands. 

Learn More
customer data digital globe thumbnail

5 CDP Shortcomings Ad Tech Brands Face & How to Fix Them

Customer data platforms (CDPs) help businesses aggregate and analyze customer data from multiple channels. As brands interact with consumers through various touchpoints, the CDP cleans and unifies the data to build more complete customer profiles.   But getting a true 360° view of user behavior remains a challenge.

Learn More
data outer space thumbnail

3 Powerful Time-Series Analysis Techniques to Drive Better Insights

Time-series data is everywhere—whether or not your brand is equipped to handle it. Data-driven organizations need time-series analysis platforms to make the most of their data, but some brands may not realize there are different techniques for achieving time-series analysis. The question isn’t whether time-series analytics platforms are worth it—they are—but knowing which analysis technique is best suited for your brand goals and needs.

Learn More

Make better decisions with 360° of data-backed insights.

Explore what a true self-service customer experience analytics platform can do for your business.

Click Here

Case studies

See All
Bleacher Report Decreases Time to Insights by 95% thumbnail

Bleacher Report Decreases Time to Insights by 95%

Learn how Bleacher Report uses Scuba to rapidly gain insights into user behavior, increase conversion and engagement, build satisfaction, and redesign their web and mobile applications.

Learn More
Edmunds Explores Journey Analytics 100x Faster on Scuba thumbnail

Edmunds Explores Journey Analytics 100x Faster on Scuba

Learn how Scuba is helping Edmunds enable self-service analytics for business users, analysts and executives - faster than complex SQL-based queries.

Learn More
Telecommunications giant logs 11.3M fewer support calls, boosts NPS, and saves millions with Scuba thumbnail

Telecommunications giant logs 11.3M fewer support calls, boosts NPS, and saves millions with Scuba

One of the largest telecomms in the world set an ambitious goal – to dramatically improve their customer experience. They wanted a real time customer experience analytics solution to tackle changing consumer demands and growing competitive pressures.

Learn More