Everyone is running behind big data these days. Professionals from varied spheres are adoring 21st-century data science. Big Data has been an ambivalent word in the IT industry for some time, but this will change shortly. Let’s see Big Data Trends to understand the big picture of big data.<\/p>\n
Gartner found in a survey that about 48% of companies invested in big data<\/strong> in 2016. Nearly three-quarters of those surveyed have already invested or planned to invest in coming years.<\/p>\n So, let’s explore top Big Data Trends.<\/p>\n Today, different sectors like marketing and pharmaceutical companies use data-driven decisions. Algorithms influence by information about shopping habits, which we use for engineering in both formula 1 vehicles & asthma drugs.<\/p>\n But has Big Data reached its peak or is there more potential to explore? Here are the top 10 Big Data predictions<\/strong> by different Big Data experts. It will help you in knowing Big Data Trends in next few years.<\/p>\n It will also help you in understanding top Big Data technologies and salary along with other Big Data trends. Looking to compare different Big Data technologies follow this comparison guide.<\/p>\n The most obvious big data prediction is that there will be more of data that will be analyzed to gain valuable insight. Forrester declares that \u2018all companies are in the data business now<\/strong>\u2019.<\/p>\n The increasing number of individuals mostly using internet shows that there is more opportunity than ever before to create and collect data.<\/p>\n By empowering the organization to make data-driven decisions at a high speed, IT will soon become the data hero who helps in shaping the future of the business. \u2013 \u201cFrancois Ajenstat, Chief Product Officer at Tableau\u201d<\/em><\/p>\n Analytics will experience a revolution in coming years. Streaming analytics is predicted to become a default enterprise capability, and there will be widespread enterprise adoption and implementation of this technology to help companies gain a competitive advantage from their data.<\/p>\n In terms of the technologies to achieve this, there will be an acceleration in the usage of open sources streaming engines, such as Spark Streaming and Apache Flink, in tight integration with Hadoop Data Lake which will provide easier approaches in leveraging open source in the enterprise. \u2013 \u201cAnand Venugopal, Head of Product, StreamAnalytix, Impetus Technologies\u201d<\/em><\/p>\n Interconnected devices are projected to hit 34 billion soon. More businesses will start exploring and exploiting their benefits to fulfill various business objectives.<\/p>\n Big data is invaluable to marketers and the IoT<\/strong> add further value to it. Along with better targeting & personalizing the marketing messages, business will be able to create more useful products for their customers. That will help unleash the real potential of some of those new technologies like IoT, machine learning and AI \u2013 \u201cChuck Pieper, CEO, Cambridge Semantics\u201d<\/strong><\/p>\n 2016 was not a good year for Hadoop and specifically for Hadoop distribution vendors. But, there is going to be an increased adoption of Hadoop. Hadoop will not replace other databases but it will be an essential part of data ingestion in the IoT \/ digital world. \u2013 \u201cGeorge Corugedo, CTO, RedPoint Global\u201d<\/em><\/p>\n As per Ashish Thusoo, CEO, Qubole<\/em>, in 2022, enterprises are expected to move their big data projects to the cloud<\/strong> in droves. Moving data to the cloud intensifies adoption of the latest capabilities to turn data into action.<\/p>\n It also enables cost cutting in on-going maintenance and operations. We expect that there will be more data on the cloud. This enables enterprises to select the analytics tools like Spark or Flink \u2013 \u201cSnapLogic\u201d.<\/em><\/p>\n More and more organizations will be adopting Hadoop and other big data stores which will rapidly introduce new, innovative Hadoop solutions. For this, Businesses will hire more big data analytics to provide a better service to their customers and keep their competitive edge.<\/p>\n This will open up capabilities for coders and data scientists that will be mind-blowing. \u2013 \u201cJeff Catlin, CEO, Lexalytics\u201d<\/em>.<\/p>\n According to the McKinsey Global Institute<\/em>, data scientists demand is growing by as much as 12 percent a year and there could be a shortage of as many as 250,000 data scientists by 2024 in US economy.<\/p>\n As per prediction by Robert half<\/em>, Data Scientist salaries are predicted to range from $116,000 to $163,500 in 2018. This is an increase of about 6.4% over 2016 salary levels. Similarly, Big Data Engineer salaries are predicted to range from $135,000 to $196,000, increasing 5.8% over 2016 salary levels.<\/p>\n Everything from social media, health monitors and taxi apps collect data from the user, to better understand customers. In order to improve top line revenue through cross-sell\/upsell or reduce churn to remove the risk of lost revenue.<\/p>\n This will have a transformative impact on the ability of a data-centric business in identifying new revenue streams, saving costs and improving their customer intimacy. \u2013 \u201cScott Gnau, Chief Technology Officer, Hortonworks\u201d.<\/em><\/p>\n Many experts have predicted that the creation of the huge volume of data & its use will result in its monetization. Michael Dell <\/em>predicted that big data analytics is the next trillion-dollar market. IDC<\/em> predicts that data monetization efforts will result in enterprises increasing the marketplace\u2019s consumption of their own data by 100-fold \u2013 or even more.<\/p>\n Thus, Forrester<\/em> expects that the number of firms will look to drive value and revenue from their \u2018exhaust fumes\u2019. IDC<\/em> predicts that by 2022, organizations can analyze all available data to deliver actionable information. This information will gain an extra $430 billion in productivity benefits over their less analytically oriented peers.<\/p>\n Regardless, business intelligence<\/strong> will no longer be considered a department but an attitude. At least for those who plan to be in business by 2022. \u2013 \u201cAnthony Dina, Director Data Analytics, Dell EMC\u201d.<\/em><\/p>\n Ultimately, it looks like big data will be bigger and bigger in coming years as compared to 2016. So, patents for innovative products, huge growth in the generated data, & increasing customer demand shows that data will be the driving force behind many business decisions.<\/p>\n Big Data, Big Opportunities, Big Impact, Big Decision, Big Scope, Big Career, Big Salary\u2026.!!!<\/p>\n Hence, this was all in top Big Data Trends. Still, if you have any query, ask through the comments tab.<\/p>\n","protected":false},"excerpt":{"rendered":" Everyone is running behind big data these days. Professionals from varied spheres are adoring 21st-century data science. Big Data has been an ambivalent word in the IT industry for some time, but this will...<\/p>\n","protected":false},"author":6,"featured_media":41910,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14],"tags":[750,782,1907,17650,1962,1972,4738,4996,5186,7841,13021],"class_list":["post-1365","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-data","tag-apache-flink","tag-apache-hadoop","tag-big-data","tag-big-data-in-2018","tag-big-data-predictions","tag-big-data-tutorial","tag-flink","tag-future-of-big-data","tag-hadoop","tag-kafka","tag-spark"],"yoast_head":"\nLatest Big Data Trends<\/h3>\n
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i. Proliferation of data<\/h4>\n
ii. Increasing Streaming Analytics via Apache Flink and Spark Streaming<\/h4>\n
iii. Increasing Data Analytics<\/h4>\n
iv. Hadoop at its Best<\/h4>\n
v. Increasing Focus on Cloud-Based Data Analytics<\/h4>\n
vi. More Demand for Big Data and Analytical Skills<\/h4>\n
vii. Hike in Salaries for Big Data Specialists and Data Scientists<\/h4>\n
viii. Improving Customer Experience<\/h4>\n
ix. Increasing Monetization<\/h4>\n
x. Achieving Maximum Business Intelligence With Data Virtualization<\/h4>\n
Summary for Big Data Trends<\/h3>\n