The New Generation: Faster and More Approachable Data Analysis Platforms

No more waiting is necessary. The next generation of analytics technologies has arrived. The focus is to be faster and stronger while being easy to use and agile.

The democratization of information technology has made a great impact on the business industry. Companies with limited knowledge of the IT domain can now launch major ventures without reservations. In particular, data is widespread—an asset giving business leaders more acumen on a multitude of developments.

Cutting-Edge Visualization Technologies

Due to the complexity and vast amount of data, visualization is now a key technology for businesses worldwide. Understanding raw data can be difficult and may require assistance from a data scientist. That’s why visual data discovery tools are important.

An upgrade from the old-school line graphs, visualization technologies offer comprehensive, interactive capabilities. In today’s world, anyone–including people without a technical background—can transform raw data into unambiguous information with easy-to-use formats. Thus, decision makers can conveniently digest the material and spot opportunities for growth in a timely manner.

An online survey discovered that 74% of business intelligence practitioners were highly influenced by data visualization for acquiring business insights within their organizations. The survey results also indicated that data visualization tools help drive increased adoption of BI dashboards, which is the preferred channel for accessing visuals.

To produce compelling data visualizations start with a mission and define your goal. Don’t forgo impact for eye candy.

Jeffrey Baumes, a data scientist at Kitware, states, “Often, those seeking visualizations are flattered more by flashy showmanship than by how the visualization draws true insight from data.”

Baumes suggests that people focus on the core message of the visualization, not the design.

For example the Analytical Document unifies data from multiple sources and enables sharing and collaboration. You can use our predefined modules, such as churn and lifetime value, or build your own and analyze anything, not just what a wizard will guide you to do.

Cloud-Based Data Warehousing

Business intelligence is better when your entire staff possesses hands-on access to data. A cloud-based data warehousing makes this possible.

Cloud services offer an alternative that can provide value. Businesses with a limited budget may realize the difficulty in maintaining an on-site data warehouse. A cloud-based platform is flexible and inexpensive.

Large-scale cloud data warehouses help organizations focus on the business and not the IT. Companies can direct their IT employees from data warehousing to other demanding responsibilities.

Based on Information Week surveys, in 2014 cloud-based data warehousing services led the information management category. The adoption rate increased from 24% to 34%.

Data warehousing is still a critical business element. The State of the Data Warehouse survey asked 300+ individuals in charge of data initiatives at public and private organizations about their experiences with data warehousing. Ninety-one percent of respondents said they’ve considered it as an investment, while just 5 percent have fully implemented a big data initiative.

In the face of security concerns with sensitive information, cloud-based technology advances are persuading companies to trust the cloud. There are two schools of thought regarding this relevant issue. Some organizations believe that keeping information internally by default keeps it more secure. Others argue that cloud providers exist to secure data. Thus, these providers offer skilled personnel, who are trained in security and compliance safeguards.

Unified Data

Your warehouse must be equipped to handle large amounts of data. In return, your business will receive better query workloads and query optimization.
When you can unify data from multiple sources, your team will understand all facets of your users’ behavior. In other words, you get the full context for your data. By analyzing your data in one unit, comprehensive business insights are more accessible.

Simplicity in Complex Querying

The need for real-time, complex querying of big data exists. SQL has governed the database sphere for years. It’s a standard query language that represents data in a common, relational table.

Avoid challenges with big data application performance by ensuring that your IT staff is ahead of the curve. Let your IT team coordinate with analysts and gather data access metrics. Continuous communication and coordination will create and maintain a good relationship.

Plan for growth in the number and complexity of queries. Complex queries require a system to determine an efficient access path. You may need to add performance-enhancing features, like indexes or data partitioning to the database.

Consider purging or archiving stale data. Sometimes, we believe more data leads to better analysis. However, some historical data can become useless. Purge reduces the total amount of data storage, and archiving allows for reloading later. Whatever you decide, reducing the size will speed up queries.


SQL isn’t always the best option for modern applications. We generate a great deal of data and For instance, querying user event data contains several messages that may seem impossible to index or store in a relational table. CoolaSQL provides the ability to examine a sequence of events, whereas SQL is more set-based. Learn about CoolaSQL in the video below.


CoolaData represents log and event-based big data in relational, schema-like structures. CoolaSQL allows for easy analysis of typical behavioral patterns, such as with path analysis, cohort analysis, and funnel analysis.

The new generation of analytics technology is already here. From visualization to complex querying, give your team the opportunity to explore different tools to grow your business.

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