Modern-day businesses operate at breakneck speeds and generate massive amount of data. Every piece of information embedded in data is priceless and it is important to act upon it fast to maximize its value. In order to extract the information, Big Data analytics are required. As Big Data tech has grown leaps and bounds in the recent years, it can prove invaluable for a business operation. But, it comes with its own challenges: processing of data being the first and foremost. Nowadays, two processing methodologies are utilized by companies – batch processing and stream processing big data. Continue reading
Maximize Insights In Real-Time With Stream Processing Applications
The world of today is extremely fast paced. And, when it comes to businesses, the pace can be unsettling for companies, especially the ones that rely on old processing methodologies. Nowadays, the reliance on Big Data is at an all-time high. To exploit Big Data benefits, the standard processing applications simply do not work. There is a need to leverage stream processing applications to counter the threat of competition.Continue reading
Improve OLTP and OLAP Performance with In Memory Scalable Transactions
Online processing has become a vital part of business operations. Whether it is processing of transactions (OLTP) or recurring analytics (OLAP), cutting-edge processing solutions have become the need of the hour. In memory scalable transactions processing allows companies in telecom and financial industry to execute vast troves of ingested data in a jiffy.Continue reading
Empower Big Data Processing and Make Timely Decisions for Business Growth
Taking business decisions at the right time makes a huge difference in any commercial endeavor. It can be the difference between success and failure, especially in this age of competition where every business has several competitors vying for the same customer base. As there are multiple dynamics that influence business decisions, it is hard to take each one of them into account during the analysis phase. Big Data processing simplifies this procedure and allows for dissection of every fact through insights that can be worthwhile for a business venture.Continue reading
Don’t Let In Memory Transaction Loads Spoil Big Data with Superfast Processing
Big Data analytics have evolved into a major requirement of businesses looking to counter the threat of excessive competition. As many companies fight for the attention of same customer base, there is a need to differentiate one from another. And, this can only be done if you have the insights required to alter your business strategies according to the ever-changing customer tendencies. To ensure timely interventions and amending a business plan on the go, it is important to manage in memory transaction loads for leveraging real-time data analysis.Continue reading
How to Make Machine Data Useful with Real-Time In-Memory Processing Solutions?
Machines play a vital role in today’s business operations. Almost every industry is automated and the reliance on machines is quite high. But, even with all the right resources, it has become difficult for a company to differentiate itself from its competitors. Using traditional methodology, it is simply not possible to evoke customer interest. However, cutting-edge analytics and Big Data are a different proposition altogether. Big Data analytics can be implemented on vast troves of data to unearth useful insights. Therefore, you should make machine data useful by employing the right tools.Continue reading
The Importance of Stream Processing Big Data for Modern Businesses
Big Data is an important part of modern-day business operations. If analyzed correctly, Big Data can help a company improve its work. It can also help them form better business strategies by providing insights relevant to customer behavior. But, to process Big Data, it is important to have relevant processing solutions. Stream processing big data offers the best platform for the analysis of large amounts of data as it employs real-time stream processing technology.Continue reading
React to Customer Interest Faster with Stream Processing Applications
Customers of today have become finicky. With access to the Internet at their fingertips at all times (thanks to the smartphones), they are able to analyze products/services faster than ever before. Social media platforms like Facebook and Twitter have transformed into information portals for customers. The wealth of knowledge derived from these platforms sways the decision of millions and shapes the fortunes of brands across the globe. For a business to prosper in the current times, it has become crucial to unearth customer interest and launch product/services accordingly. This is where Big Data analytics and stream processing applications come into the picture.Continue reading
Analyze Security Logs to Improve Security Standards with Scalable Solutions Processing
IoT has been the buzzword in the telecom industry for almost a decade. Although analysts remain brutish about its potential to succeed in the coming time, it has not hit the stratospheric peaks that were expected of it. As we speak, IoT sensor chips are getting modified for added security, hardware manufacturers are hard at work to improve the processing power of chips and the versatility in Internet connectivity (for addressing the different requirements of different IoT use cases) has increased considerably. But, the main issue with IoT still remains security that needs to be bolstered with robust security measures. The need for a large and scalable solutions processing platform that can analyze security logs and provide insights about any loopholes in the security has become the need of the hour.Continue reading
Leverage Big Data Analysis and Get Improved Insights with Massive Data Processing
Staying one step ahead of the game at all times is the key to success in modern-day business environment. As data generation via online platforms reaches an all-time high, the need to put it to good use is growing. Massive data processing solutions have become the need of the hour and the need for data stream processing is at an all-time high.Continue reading