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Overcoming Real-Time Data Integration Challenges to Optimize for Surgical Capacity


In the healthcare industry, surgical capacity management is one of the biggest issues organizations face. Hospitals and surgery centers must be efficient in handling their resources. The margins are too small for waste, and there are too many patients in need of care. Data, particularly real-time data, is an essential asset. But it is only […]

The post Overcoming Real-Time Data Integration Challenges to Optimize for Surgical Capacity appeared first on DATAVERSITY.


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Author: Jeff Robbins

9 Best Practices for Real-Time Data Management


In the era of digital transformation, data has become the new oil. Businesses increasingly rely on real-time data to make informed decisions, improve customer experiences, and gain a competitive edge. However, managing and handling real-time data can be challenging due to its volume, velocity, and variety. This article will guide you through nine best practices […]

The post 9 Best Practices for Real-Time Data Management appeared first on DATAVERSITY.


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Author: Anas Baig

Architecting Real-Time Analytics for Speed and Scale


In today’s fast-paced world, the concept of patience as a virtue seems to be fading away, as people no longer want to wait for anything. If Netflix takes too long to load or the nearest Lyft is too far, users are quick to switch to alternative options. The demand for instant results is not limited […]

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Author: David Wang

Real-Time Data Analytics During Uncertain Times

Are we in a recession? Not in the U.S., according to some economists, a recession is defined as two consecutive quarters of negative gross domestic product (GDP) growth. But most will agree that we are living in uncertain times with the recent failure of two large banks, inflation, widespread layoffs in the technology sector, and geopolitical uncertainty. As a result, the top worry for most CEOs in 2023 is a recession or an economic downturn, according to a recent survey from The Conference Board.

In response to economic pressures, many companies are examining their technology spending more closely, and data analytics is no exception. However, analytics provides the opportunity to deliver more business value than what it costs, and this becomes even more important when an organization’s bottom line is under pressure. Here are just a few areas where data analytics has a huge impact by providing real-time insights that help businesses optimize their operations to increase revenue and cut costs.

Optimizing Pricing and Promotions: By analyzing customer behavior, purchasing patterns, market trends, and competitor pricing, businesses can identify the best pricing strategies and promotional offers to increase sales.

Acquiring and Retaining Customers: Analyzing data can help businesses know their customers better to develop targeted strategies and deliver personalized customer experiences that win new business and prevent customer churn.

Identifying Process Inefficiencies: Data analytics can help businesses detect areas where processes need to be optimized by identifying bottlenecks, and areas where resources are being wasted or where the business is overspending.

Improving Forecasting and Planning:  Businesses can use analytics to predict future sales, which leads to better production planning.

Detecting Fraud:  Detecting fraud with analytics helps avoid financial losses and reduces the costs of investigating and resolving fraud cases.

Reducing Energy Spend: Businesses can analyze energy consumption to reduce energy waste, lowering energy bills.

Increase Employee Productivity:  Analyzing employee data can help identify where employees are over or under-utilized to reduce costs and improve productivity.

Improving Forecasting and Planning:  Businesses can use analytics to predict future sales, which leads to better production and inventory planning.

Assessing and Managing Risks: Risk management analytics helps spot trends and weaknesses and provide insights into the best way to resolve them proactively.

Connect Business Value with the Cost of Business Analytics

Cost does matter. In today’s uncertain times, data analytics initiatives must align costs with business value more than ever before. However, you need to focus on cost optimization rather than cost-cutting. A cost-optimal solution should not only process analytics workloads cost-effectively, but also include data integration, data quality, and other management workloads that add more costs and complexity when sourced from multiple vendors.

The Actian Data Platform provides high business value at low cost. It’s built to maximize resource utilization to deliver unmatched performance and an unbeatable total cost of ownership. Plus, it’s a single platform for data integration, data management, and data analytics. This translates into lower risk, cost, and complexity than cobbling together point solutions.

Watch our webinar, “Maximizing Business Success in an Uncertain World with Real-Time Analytics” to see how the Avalanche platform delivers the analytics decisions makers need in an uncertain world.

The post Real-Time Data Analytics During Uncertain Times appeared first on Actian.


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Author: Teresa Wingfield

REAL Real-time Data Analytics: When Seconds Matter

According to Gartner, real-time analytics is the discipline that applies logic and mathematics to data to provide insights for making better decisions quickly. For some use cases, real-time means analytics is completed within a few seconds after the arrival of new data. Actian calls this REAL real-time data analytics.  

Analytics solutions vary greatly in their real-time capabilities, with many having only “near” real-time analytics. REAL real-time analytics means that you can immediately deliver real-time data and consistently execute ultra-fast queries to inform decisions in the moment. Here’s a quick overview of how the Avalanche Cloud Data Platform achieves these two requirements.   

Real-time Data 

Real-time data is information that is delivered immediately after collection. This requires real-time, event and embedded processing options so that you can ingest your data quickly. You will also need integration that includes orchestration, scheduling, and data pipeline management functionality to help ensure that there is no delay in the timeliness of information.  

The Avalanche Cloud Data Platform is noted for its fast delivery of real-time data using the above data integration features. In a recent Enterprise Strategy Group economic validation, customers reported that the Avalanche platform reduced data load times up to 99% and reduced integration and conversion time up to 95%. 

Real-time Queries   

A columnar database with vectorized data processing has become the de facto standard to accelerate analytical queries. While row-oriented storage and execution are designed to optimize performance for online transaction processing queries, they provide sub-optimal performance for analytical queries.  

A columnar database stores data in columns instead of rows. The purpose of a columnar database is to efficiently write and read data to and from hard disk storage to speed up the time it takes to return query results. 

Vectorization enables highly optimized query processing of columnar data. Vectorization is the process of converting an algorithm from operating on a single value at a time to operating on a set of values (vector) at one time. Modern CPUs support this with Single instruction, multiple data (SIMD) parallel processing.  

Additional optimizations such as multi-core parallelism, query execution in CPU cores/cache, and more contribute to making the Avalanche Cloud Data Platform the world’s fastest analytics platform. The Avalanche platform is up to 7.9 x faster than alternatives, according to the Enterprise Strategy Group.  

The Avalanche platform also has patented technology that allows you to continuously keep your analytics dataset up-to-date, without affecting downstream query performance. This is ideal for delivering faster analytic outcomes. 

When Seconds Matter 

So why does speed matter? Real-time data analytics allows businesses to act without delay so that they can seize opportunities or prevent problems before they happen. Here is a brief example of each type of benefit.  

Online Insurance Quotes 

Insurance comparison websites in the UK give top billing to insurers who respond fastest to online requests for quotes. Insurance uses the Avalanche platform for real-time analytics to deliver a risk-balanced, competitive insurance quote with sub-second speed. 

Proactive Equipment Maintenance  

As manufacturers incorporate more IoT devices on their plant floors, they have opportunities to analyze data from them in real-time to identify and resolve potential problems with production-line equipment, before they happen, and to spot bottlenecks and quality assurance issues faster.  

The Avalanche Cloud Data Platform a single solution for data integration, data management, and real-time data analytics. Check out how the platform lets you integrate anytime.  

The post REAL Real-time Data Analytics: When Seconds Matter appeared first on Actian.


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Author: Teresa Wingfield

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