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The value of improved data analytics, integration and visualization has surged in importance in recent years, highlighted by many recent acquisitions of companies in the space. CIOs should prioritize team education, modern toolsets and processes to take advantage of all of the changes in this market.
Organizational leadership across all sectors are learning how vital data can be to business growth and profitability. CIO’s are often first tasked with the mission to collect, organize, and understand data to help the C-Suite as a whole make more intelligent decisions. To turn data into insights, it must be analyzed.
Future-thinking CEOs understand that data literacy allows businesses to see better returns on their investments, boosts in revenue, and optimizations, which in turn helps CIO’s to justify additional budget to acquire talent with the required skillsets and implement modern tools.
How businesses are investing in data science and analytics
With the rise of the cloud and IoT (Internet of Things), a wide range of applications and devices now generate data, at ever higher volumes and with ever greater complexity. This volume and complexity demand efficient, scalable solutions to the integration, storage and analysis of data. The most efficient approach to this challenge is to host data operations in the cloud, rather than on-premise.
According to IBM, only 20% of an average company’s data workload has migrated to the cloud, despite its benefits. This means that there is a great deal of untapped potential for data integration solutions.
There have been several recent acquisitions that demonstrate the rising value of data science and analytics. Salesforce and Google have both recently acquired firms specializing in data analysis. Google acquired Looker, a business intelligence startup, for $2.6 B. Through this acquisition, Google hopes to merge its cloud-based capabilities with Looker’s to create an “end to end data analytics solution.”
Tableau, a data analytics company, was acquired by Salesforce for $1.57 B The goal behind this acquisition is to increase customers’ ability to visualize and analyze their data by merging Tableau’s data-based offerings with Salesforce’s understanding of customer behavior.
There are also tools for making data migration to the cloud easier. According to Charles Wang of Fivetran, there are more data sources than ever before, and it’s critical to make moving data to the cloud easier for businesses to allow organizations immediate access to a data pipeline. Because of its pre-constructed schemas, data analysts are left with more time to mine data for the information needed to move the company forward. It saves time, money, and gives companies the means to be more literate with their data. With Fivetran, data analysts can immediately access data and run queries, thereby spending more time gaining insights rather than on data extraction.
Lyftron is another company that recognizes the need for organizations to control their data without wasting time and resources on engineering data pipelines. It automatically converts data into a ready-to-query format, making it possible for analysts to provide more value.
The increased need for data science careers
Per Statista, the big data market is growing rapidly, with $42 B USD revenues in 2018 and a massive increase to an expected $1.89 B in 2019. Per the same study, nearly 60% of the companies that deployed big data strategies reported actually reducing overall expenses due to the effort and 40.3 percent of respondents suggested that big data adoption was held up by a Lack of organizational alignment or agility. Corporations are adopting new technologies to help manage integration and draw insights from big data. In the telecommunications industry alone, around 94.5 percent of respondents representing the telecommunications industry stated that their organization currently used big data technology as of 2018.
The aforementioned acquisitions and increasing awareness of the need for astute data analysis experts mean that more and more companies will target employees who can effectively fill those roles.
The careers data specialists can pursue are expanding, allowing for greater technical diversity. As the number of roles in the industry grows, so does the need for specialization. Careers are becoming more specific, with organizations seeking expertise in one particular area over broad technical knowledge.
More people are pursuing educational paths in the realm of data science and analytics as well. There are now more options for those interested in data-based careers, including online courses and boot camps, as well as more traditional bachelor’s and master’s programs. According to LinkedIn, there has been a 56% increase in data scientist job openings in the US since 2018, and a recent report by Indeed revealed a 29% year-over-year increase (and 344% increase since 2013). Aside from the many business insights that can support sales, marketing and product development, mining user data and making it available to fuel artificial intelligence and machine learning is considered the new gold rush by many venture capitalists. As companies increasingly compete in the talent pool for data scientists and expert analysts, more universities are offering degrees in data science to meet the increasing demand.
Data analysis is crucial to making informed business decisions. According to SAS, 72 percent of respondents surveyed said that analytics provided them with valuable insight and 60 percent said that data analytics allowed them to better innovate. Businesses are investing in the tools and teams necessary to understand and organize their data for success.