The top trends in big data technology are Big Data Analytics, Big Data Platforms, Cloud Computing, and Big Data Service Level Agreements.” The top trends in big data technologies are increasing data storage capacity, leveraging data analytics, delivering customized solutions, and enabling artificial intelligence. One key trend is missing from the top five trends list, and it’s called spark.
Spark
We heard about it last year when Netflix added full-fledged streaming video to their massive data ingesting cache. The main advantage of elasticsearch is real-time data analytics, and it’s also known as hotlisting in the industry.
Hotlisting allows an application like Netflix’s streaming video to be highly-scalable. As a result, Netflix can scale their video ingesting up to several terabytes per second without worrying about the performance issues of streaming large amounts of data.
Real-Time Data Analysis
The second trend is real-time data analysis. Facebook’s sidebar widget, for instance, is built on top of elasticsearch and supports full-text attribute extraction, stemming, and ranking.
Facebook has many other real-time data analytics tools such as graph databases, visual analytics, and news feeds. Compared to traditional time-based data analysis tools such as SAS and SQL, it’s easy to see why big data technologies are rapidly replacing them.
Operational Big Data Technologies
The third trend is operational big data technologies. Operational big technologies refer to tools and systems that help organizations work more efficiently. These systems and tools can be integrated into companies’ workflow, automatically allowing social media managers to share information across multiple channels.
These functionalities can create customer relationships, generate leads, automate sales processes, manage customer service calls, and track employee productivity. These are just a few examples of how operational big data technologies can improve companies’ bottom line.
Artificially Intelligent Technologies
The fourth trend is artificially intelligent technologies. Artificial intelligence, short for artificial superintelligence, was first mentioned in the 1990s with the development of the AI computer.
Today, artificial intelligence systems and tools are playing an increasing role in everything from stock trading to healthcare to transportation. While the technology itself hasn’t yet reached the point of replacing humans completely, there are numerous ways artificial intelligence is helping businesses today. That’s where ONPASSIVE started building fully autonomous products aiming to help businesses in achieving success.
Predictive Analytics
The fifth trend is the topmost big data technologies like predictive analytics. This type of technology can be used to analyze and make predictions about customer needs. For example, some companies use predictive analytics to predict how quickly and efficiently products will be sold to ensure they don’t sell too fast and have too much inventory.
Integration Of Knimee
The sixth trend is the integration of Knimee. Knimee is a data analytics platform capable of delivering insights from a massive amount of data to give relevant insights into business strategies.
For example, Knimee can analyze customer service data to suggest creative solutions to customer issues. In addition to helping businesses provide superior customer service, Knimee’s technology also allows them to explore and make decisions about e-business products and services.
Artificial Intelligence And Distributed Intelligence
Finally, the seventh trend is artificial intelligence and distributed intelligence. Several industries are leveraging artificial intelligence and distributed data technologies to improve their process and improve the productivity of their employees.
For example, medicine has successfully used sophisticated artificial intelligence technologies such as metabolomics, sequencing, and pharmacogenetics to diagnose, treat, and prevent diseases. Similarly, manufacturing automation systems have grown increasingly more intelligent and automated over time, allowing factories to produce more efficient products at a reduced cost.
Big Data And Sqoop
The eighth and ninth trends are based on two super-specialized systems: Big Data and Sqoop. Both these systems are incredibly complex and very difficult to deploy. However, they have tremendous value in understanding, organizing, managing, and sharing large amounts of data. The primary benefit of the Big Data system is that it allows for greater insight into product and business strategies.
Sqoop, on the other hand, is a system designed to enable easy access and collaboration between different systems – including social networks and online stores.
Concluding Words
In conclusion, there are several important trends in cloud computing that we will be covering in future blog updates. However, our primary focus is to highlight the importance of scalability and metasocket integration for both SaaS and on-premise data warehouses.
Our upcoming blog post will focus on metasocket scalability, explicitly using Google’s Dataflow and Spark to rapidly scale up a data warehouse.
If you’d like to learn more about developing custom software, we hire a full-time Software Engineering Team from Vancouver, Canada. Our goal is to build the best software possible while building it for the cloud.
As a cloud developer and Consultant, we believe that the best way to achieve this goal is to bring your business logic into your cloud development environment. It allows you to scale your requirements and improve your process efficiency quickly. To find out more, check out our cloud blog.
