From groundbreaking new device capabilities to a whole new approach to mobile apps to wearable tech to more hand-in-hand collaboration with the evolving world of Internet of Things, the last 2 years have played an important role in the innovations of new technology and interfaces. These two years observed a sustained focus on enterprise mobile apps which have grown beyond leaps and bounds. A whole range of era changing mobile gadgets like fitness trackers, Google Glass, Apple Watch and Android Wear came to push the boundaries of mobile technology further. With the introduction of Apple Pay and Google Wallet, the empowerment of mobile as digital wallet became a reality. While there is no sign of stop to this fast evolving tech landscape, 2016 is going to observe an array of defining trends for the developers.
As far as making predictions for developer trends as far as the upcoming year is concerned, it is still too early. But already many of the tech trends and developer leanings have become clear and we can assuredly predict a few of them. Listed below are 6 developer trends that are going to rock 2016.
1. Apache Spark is going to rule enterprise data
Apache Spark won the favor of data engineers and developers worldwide as the most well equipped open source big data processing framework that is built for offering faster processing speed, utility and sophisticated analytics. The best thing about Spark is that it offers highest ease in accessing data across the enterprises. While large businesses have really challenging volume of diverse data sets across different databases of their IT infrastructure, Spark makes it extremely easy to access all these data as per relevance and point of interaction.
Typically Spark offers the alternative to craft an algorithm to access data across large datasets. While crafting an algorithm could take days and months for a data scientist, Spark offers the required level of accessibility in just minutes saving huge on cost and time. A system based on Spark Apache can just offer seamless and transparent accessibility to data and robust analytics to analyze any database replacing the need of any additional maneuver for the same.
- Spark can make use of all major file systems for managing Big Data including Hadoop file system (HDFS), Cloudera (CDH), Hortonworks (HDP) and others.
- While Spark offers easy deployment, it facilitates large scale automation replacing the need for manual monitoring.
- Spark offers robust capability for analytics workflows.
- Spark utilizes memory more efficiently than all other earlier data management systems.
2. Real time everything will be a reality
While real time analytics continues to excel, the coming years will observe the power of real time in almost everything. 2016 is expected to be the year when every digital maneuver will strive to incorporate real time capability, though it may take a couple of years more before we can see the power of true real-time everything. From real time data sharing to real time collaboration across devices, platforms, gadgets to real time analytics, diverse interaction points of worldwide digital data will offer more fluid maneuvers to communicate, collaborate and act.
- Every digital move having real time edge will transform the way business is done along with relationship with suppliers, customers, and all stakeholders.
- More real time collaboration will increase the productivity by leaps and bounds.
- Real time everything will make business intelligence deliver insights faster and ahead of time.
3. Cloud based apps will rule
Cloud based apps in their first avatar were viewed to enhance accessibility from diverse devices and locations. Now, with the Big Data analytics and engines like HADOOP, being on the Cloud will continue to be more powerful. There are other reasons as well. Thanks to cloud support developers will be able to keep the actual app size small and consequently will be more apt to solve the memory and bandwidth issues. Moreover, cloud based analytics engines will continue to grow as digital data volume is increasing at skyrocketing speed.
- More numbers of wearable tech devices will need more cloud syncing capability.
- For driving speed and performance keeping app size smaller is a challenge and that can be handled effectively by cloud apps.
- Cloud based data analytics is the future as traditional data infrastructure seems inept to handle increasing data volume.
4. Enterprise mobile apps to beat consumer apps in revenue
In the last couple of years, enterprise mobile apps took the center stage of development. The increasing focus of businesses to develop their own business apps also paved the way to new trends like rapid development. According to experts, around 35% of all big businesses across the world would have their very own app development platforms by 2016. For third party developers this is going to open a vista of opportunities. Already in respect of earning enterprise app developers are way far ahead of their consumer counterparts. Third-party enterprise app developers stand to gain in such a scenario. The increasing reluctance of average users in spending money on mobile apps will continue to make enterprise apps more lucrative for developer companies, and by 2016 the total revenue generated from enterprise app ecosystem is likely to take over the revenue of consumer apps.
- From big businesses to brick and mortar stores all are leaning to have their own business app.
- The reluctance for spending in consumer apps is continuing to increase.
- Native apps are losing importance as mobile web is getting stronger and richer.
- Third party developers are leaning heavily on enterprise apps as more businesses are taking mobile apps seriously.
5. More powerful predictive analytics with Deep Learning
Big Data analytics is already the biggest horizon for both present and future tech trends to be occupied with. Big Data combining with high end computing power is opening new areas of analytics comprising behavioral data analytics and machine learning. In the last few years we have seen the emergence of powerful device sensors and location technology to offer real time information regarding user movements and user behavior. This granular level user data is continuing to open new opportunities for gaining insights for marketers. With new technologies like in-memory computing and machine learning going to offer more power to analytics, 2016 may see some robust strides in the direction of more predictive data analytics. New set of machine learning techniques called as Deep Learning is going to play decisive role in solving business problems without needing much human interference.
- In-memory computing and new data management technologies add to the firepower of analytics.
- Machine learning and automated algorithms will pave the way to more automated analytics needing least manual intervention.
- Data analytics across the digital world will no longer know any boundary of specialized focus as organizations would not keep sparse data aside for gaining relevant insights.
6. NoSQL databases will grow in importance
NoSQL databases refer to alternatives of traditional databases. NoSQL is the abbreviation of “Not Only SQL”. As the analytics is getting important, NoSQL databases are becoming more popular as they are more versatile tools for being used in different analytic applications. With the focus on analytics is likely to grow in all directions, the increasing popularity and adoption of NoSQL databases seem to be obvious in 2016 and beyond.
- NoSQL databases are specialized and each offers a specific analytics tool corresponding to the data.
- Specifically purpose driven, high performance and lightweight: these 3 positive attributes go in favor of NoSQL and its continuous growth and popularity.
The above predictions seem big as we see the tech world to lean towards them. Though 2016 is still couple of months away, these trends irrevocably sound strong and definite.