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Home » Trend Reports » Outlook 2018: Data Technology Trends that will redefine the way Companies do Business

Outlook 2018: Data Technology Trends that will redefine the way Companies do Business

In the ever-changing IT landscape, 2017 was no different. This year has witnessed many disruptive technologies emerge and make headlines worldwide. Terms like Artificial Intelligence, Machine Learning, Cloud and Blockchain became the brainstorming topics of discussion for boardrooms across the world. These technologies will continue to impact businesses and will certainly become integral parts of companies’ plans to lead in the future.

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The machine learning market is expected to grow from USD 1.41 billion in 2017 to USD 8.81 billion by 2022, at a CAGR of 44.1% globally.  Why? In past years, the rapid increase of large and multidimensional data sets, proliferation towards data-based real-time problem solving and rising demand for sophisticated algorithm platform along with advanced tools contributed to and will keep contributing towards the adoption of machine learning across the globe in the coming years.

By keeping all the hot phenomena in mind, Ashutosh MehrotraBusiness HeadAPAC Region at Toovio, has highlighted three key trends in “data technology” that are likely to dominate discussions and will have an immense impact on how companies will be doing business in 2018.

Companies will look for an Advanced Decisioning Platform that can- “Sense”-“Comprehend”-“Act”

Data analytics and business intelligence will play crucial role in the overall business strategy to make better and faster business decisions. Companies will continue to leverage the power of data analytics and look for “top line” to be specialized in the field of data science.

Undoubtedly, Machine Learning (ML) has come a long way in the past few years and has changed the way companies look the way they need to do business. From voice-powered personal assistants like Siri and Alexa, to more underlying and fundamental technologies like behavioral algorithms, suggestive searches, network optimization, pattern analysis, fraud detection, customer identification, churn prediction, recommendation engines, etc., these are a few examples and applications of ML in use today.

Technological advancement has made almost everything possible. From accurately predicting Customer Lifetime Value (LTV) to pinpointing a customer’s preference and populating the best offering, network operators are truly reaping the benefits of continuous improvement in targeting the right audience at the right time in the right channel and with the right content by implementation machine learning techniques. Since powerful predictive capabilities came into existence, companies are investing heavily on voice assistants, chatbots, and other intelligent business processes.

Companies will head towards “Hybrid Multi-Cloud”

Why will companies look forward to it? Moving to a hybrid cloud environment helps organizations save money and become more efficient and agile. It offers multiple level of flexibility, scalability, security, and reduced latency. Most importantly, cloud service providers are incredibly reliable, maintaining up to 99.999% uptime. Another benefit of cloud based infrastructure is that cloud drastically reduces capital expenses and downtime is the rarity. Organizations need not invest in hardware, facilities, utilities, or building out a large data center to grow their business thereby leading to zero capital investment and low maintenance.

Companies have already started moving to “Hybrid Cloud” and will keep leveraging the benefits.Gartner estimated that by 2020, cloud adoption strategies will influence more than 50 percent of IT outsourcing deals. The largest market will be the SaaS market, which will double to $75 billion by 2020.

That said, this will be a productive year for data technology companies who offer Software as a Service (SaaS) on cloud deployment. Moreover, it will be the year for companies who work on an automated machine learning methodology and provide real time interactive management platform addressing customer behavior through cloud based services for consumer based companies.

Predictive Analysis to offer Radical Discoveries

Data will continue to be the “King” and will play a crucial role in predictive analysis. The way data movement has taken over in a short span, is something C-Suite and technology analysts are embracing. In the last few years, companies have been undergoing data-driven digital transformation and leveraging data as a strategic asset. Data-driven decision making has caught fire as companies find ways to use the vast amounts of data they collect to gain a competitive edge for better service and a better-quality experience for their customers.

According to an estimate by the International Data Corporation, “global data doubles in size every two years and by 2020, it will reach over 44 trillion gigabytes.” Witnessing the data explosion at this rate, businesses will look for various ways to stay competitive.

Predictive analytics connects people for greater predictive power and high-impact insights. It enables leaders to make radical discoveries about their companies and dissect and solve complex business challenges. As a result, companies offer better business strategies leading to higher productivity and performance. Several mounting ingredients promise to further spread prediction even more ubiquitously: bigger data, better computers, storage sufficiency, wider familiarity, and advancing science. We’ll witness more prediction usage and involvement in time to come. Data-driven businesses are the way of the future for companies competing in today’s era of big data.

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