Dealing with Big Data
Every business or corporation in the modern world is keen to keep up with the latest, whether it relates to information, techniques and strategies, tools and gadgets, etc. This helps it to stay in line or even a step ahead of its competitors. Towards this end, establishments keep in regular touch with social media, trends in e-commerce, the Internet of Things, etc. As a result, the volume of data that wends its way into their data stores only keeps growing day after day. This is Big Data, visualized in the form of gigabytes/megabytes/kilobytes/terabytes/petabytes on computer systems. Since the kind of data that arrives is varied in nature, as well as rapid in its pace, organizations face all manner of challenges while dealing with Big Data.
If the growth of data is so quick that its speed of arrival is doubling every couple of years, then, one can well imagine the huge problems created with safe storage. It is necessary to store every bit of information until an establishment finds time to sift through it and differentiate between what is relevant and what is irrelevant. There is further compounding of this problem by the fact that a large part of this information is unstructured data. By unstructured data, we mean photographs, videos, documents, audios, etc.
Currently, several innovative technologies are coming into play for dealing with this issue. For instance, it is possible to scale hardware via the utilization of software-defined facilities. It is also possible to go in for hyper-converged and converged infrastructure. In case the establishment wishes to cut down on costs and space for storage, it can take recourse to a tier system, compression, or de-duplication.
Provision of Timely Insights
Now, it does not enough provide space for storage of big data. It is equally essential for the experts in analytics in any establishment to go through this data as meticulously as possible. This will enable them to provide insights that will help their respective companies to grow. Furthermore, these insights have to come into display in a timely manner.
Note that every business, big or small, has its goals to achieve. These goals may even need modifications occasionally. Then again, new goals come to take the place of the old, soon after the company delivers them. A few examples of such targets include developing innovative ways of functioning, the cost-effectiveness of each project, providing new products or services to the local and global marketplace regularly, initiate a data-driven culture at the workplace, etc. Therefore, the experts have to be on their toes all the time. They have to remember that the contemporary business world is a highly competitive one.
How are they coping with this challenge?
The analytics department in any organization is taking recourse to tools, such as artificial intelligence, Spark, NoSQL databases, significant data analytics software, machine learning, Hadoop, and business intelligence applications. Researchers and developers of software programs are looking into ways to generate reports speedily, too, such that real-time analytics aids in rapid responses to whatever is happening in the marketplace.
Who are the Experts?
Obviously, any organization will need a team of people who are perceptive, skilled, acquainted with technological advancements and their operations, and eager to keep them abreast of everything that is happening in the immediate and remote environments. They have another qualification, too – a degree in Data Science. In other words, this will be a team of data scientists, who know their worth and will demand high salaries. In fact, one may achieve a degree in Data Science too nowadays. Fortunately, for them, many organizations are willing to set aside a budget specifically for recruiting talented people, as well as training them. At the same time, they are striving to recognize and enhance talent from within the establishment too.
As if this were not enough, companies are exhibiting an eagerness to purchase analytics solutions that are equipped with machine learning or self-service functions. Thus, people without degrees in Data Science may utilize them comfortably too.
Integration of Data
Considering that big data streams into the organization via diverse sources, it is a huge challenge to integrate it. For instance, employees prepare their daily, weekly, monthly, quarterly, or yearly reports. Then again, the company avails information from social media streams too. E-mail systems, enterprise applications, mobiles, etc., are other sources. Naturally, the integration of big data for the preparation of factual, precise, and concise reports does not prove to be an easy task at all.
Once again, different tools come into play, thanks to the creative minds of different vendors. They carry the labels of data integration and ETL tools. Regardless, data integration remains a genuine problem, and software programmers are still grappling with ideas on dealing with it successfully.
Closely associated with this issue is the one focusing on the validation of data. Many times, an establishment finds itself viewing similar scraps of data forwarded by diverse systems. To make the matter more complicated, the similar-looking data from one system may not exactly match the one from another system. To illustrate, an enterprise resource planning system and the e-commerce system may exhibit different numbers regarding daily sales. Anyone, preparing a report dealing with sales, will be confused! Therefore, it is imperative to have a team take charge of data governance. This team will be responsible for formulating policies, processes, and technology usage.
After doing so much hard work, if an organization should find its data store hacked or corrupted, it would be akin to a terrible disaster! Therefore, organizations strive to keep their big data safe and secure through the usage of data encryption, identity and access control, data segregation, etc.
Although there are all kinds of technologies to deal with significant data challenges, there are none to deal with the biggest problem of all – human resistance. Surprisingly, the majority of businesses fail to comprehend the importance of managing big data effectively, such that they achieve their goals quickly. If they view and do things differently, software developers will gain the impetus they need to come up with more significant and more practical innovations.