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How Cloud Computing Is Changing, The Way We Interact With Data

How Cloud Computing Is Converting, The Approach We Have interaction With Knowledge

The rise of big data and cloud computing enabled many technological innovations and changed our perception of data. These two advancements complement each other and offer opportunities for companies and organizations to develop and succeed in today’s cutthroat digital age. To illustrate this notion, here are some interesting statistics about the data-world we currently live in:

  • There are 3.8 million searches on Google within each minute
  • Every day, over 294 billion e-mails are sent worldwide
  • A connected car produces 4 terabytes of data daily
  • 463 exabyte of data will be created every day by 2025
  • By the way, 1 exabyte consists of 1 000 000 000 000 000 000 bytes

These colossal numbers only prove how the cloud environment will only grow and provide endless possibilities for businesses, whether small companies or large enterprises. Here we present how the interaction between data and cloud computing interconnects with businesses and generates changes on a strategic and operational level.

1. The work structure becomes more flexible

Changes in the organizational structures have been noticeable with the introduction of cloud in companies’ structures. Data stored in the cloud-enabled organizations to become more adjustable since rapidly traveled information across computer systems became far more flexible. In essence, this flexibility enabled rapid data collection, monitoring, and analysis, followed by changes to products or services. Ideally, products can be adjusted to anticipate customers’ needs while closer collaboration between IT and other units such as finance or sales enables agility to manage and work with data.

“It’s already changing organizations by moving IT from a cost center to something with a place at the table in a lot of different meetings,” stated Chris Jackson, head of cloud platforms at Pearson, for Harvard Business Review.

This higher adoption of cloud solutions brings better accessibility to data as we no longer need specifically trained employees that can pull needed insights from traditional on-premise applications. With the introduction of cloud BI, organizations have started to generate insights on-the-go without the need to be physically present in the location or request additional assistance from the IT department. The online nature of the cloud also enables sharing of information through various devices that increase the amount of flexibility in interacting with data. Employees no longer need access to the on-site server, but through link sharing options, access to data is much more comfortable without the need to send heavy e-mail files.

Scenarios such as sharing documents with colleagues across the world has become a standard in today’s working environment. We simply click on a share button, and data is presented in a different continent in a matter of seconds. This unparalleled mobility increases the effectiveness of the workflow, flexibility becomes a standard while interaction with data effective.

2. Data analysis and processing is getting faster – real-time interaction

In traditional systems, data management took a significant amount of time and resources. Now, unstructured datais easily digested into structural information, making the data processing faster than ever before. This is especially true for the realm of social media, where chaotic data such as videos, tweets, posts or photos, can’t be processed under a single category. Cloud computing and big data platforms enable data processing equally available to large, medium, and small businesses across the world.

Data transfer, as mentioned earlier, is done with just a few clicks, enabling connectivity between remote sites with just one prerequisite: Internet connection. We can then process and analyze data from data stored on the cloud without the fear of losing it due to external factors, such as heavy thunderstorms or similar natural disasters.

The amount of data that needs to be processed is increasing exponentially, leaving no time for companies to stay behind these changes. Interacting with data on a real-time basis is possible due to powerful technologies behind cloud computing. Predictive analytics is used to forecast future outcomes, machine learning techniques to recognize data patterns while neural networks enable intelligent alerts used to detect data anomalies. This real-time (and future) interaction with data enables analysis that expands traditional means of making sense of insights (let’s not forget spreadsheets and endless document scrolling to find the right information). Also, the traditional infrastructure of managing and storing data is proving to be much slower (think of weeks or even months to install and run a server). Cloud computing is providing companies with all the needed resources for effective data management.

While there are certain setbacks of storing data in the cloud, the challenges of cloud computing, mainly including security issues, migration, and governance among others, still don’t overpower the benefits of these solutions.

3. Decision-making is supported by artificial intelligence

Cloud computing enabled the development of advanced systems such as artificial intelligence. In business practice, these systems determine how to optimize business layouts, and the majority of them work through the cloud. An interesting example would be the logistics industry, where robots pick and pack production elements, ensuring the best possible outcome for the production process – the machines send their data to the cloud and interact through a unified cloud system. Essentially, robots can alert the system when inventory is on lower levels or there is an issue in the process, helping in monitoring the selected logistics KPI.

These cases of technologies talking amongst itself enable human counterparts to effectively reduce the time to make an adequate decision while storing all the data on the cloud. Workers are immediately alarmed, making the automation of collecting data and advanced robotics a more effective process in warehouse operations, decreasing the time for troubleshooting and enabling smooth operational processes.

Streamlining routes is another advantage in the decision-making processes of the logistics industry. The time and energy needed to effectively manage shipping routes have been one of the biggest challenges in this sector. Less than truckload (LTL) shippers are trying to fill their vehicles with packages going to similar destinations to minimize the fuel spent, amount of time spent on the road, and the number of stops a trucker needs to make. Data collection and cloud computing make this process much smoother by utilizing systems that automatically suggest the most efficient shipping routes for various retailers.

The design of these effective decision support systems make room to interact with data in a way that business activities become much more cost-effective to find and solve business issues. This modern form of communication between artificial intelligence and humans will certainly grow in the future and create even more opportunities to gather, monitor, and analyze large datasets for effective decision-making processes.

4. Data science is becoming indispensable

Cloud computing and data science essentially go side by side. With the development of data science in the last 30 years, companies invest more into qualified employees who can investigate structured and unstructured data, no matter the size or format, and analyze to draw actionable insights. The cloud enables an inexpensive solution to companies which don’t want to invest in giant on-premise solutions, but are looking for SaaS (software-as-a-service) means of storing and managing their data.

According to TechJury, there will be more than 64 billion Internet of Things (IoT) devices worldwide by the year 2025. The data generated by this interconnection, most of it available on the cloud, evokes the need to be flexible with disparate data sets by using data science as a means for connecting information that is stored online with insights needed to obtain a sustainable business operation. The benefits of using virtual machines in the work of data scientists are that they can be tailored to the computing and data storage requirements.

The compelling intermingling between cloud and data forms the foundations of digitization. The cloud is vital for various applications and data. Essentially, the cloud has become a virtual assistant for companies to utilize its power without worries about storage and time. Data can be shared, interacted with in many ways, easily accessed and scaled depending on the business’ needs. This way of interactivity with data wasn’t possible until recent development in technologies and services that act as a bridge between human and computer communication. The next decades will certainly bring more changes and development that we now cannot imagine, but are certainly excited to see.

This post was written for Adeptia by a guest author, Sandra Durcevic. Sandra is a Content Manager at the software company datapine. Her expertise isfocused on business intelligence, data, analytics, and technology while strivingto deliver the most knowledgeable and useful information to readers.

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