Data Blunders? How to Avoid Them!
February 15, 2021
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by Arabella Seebaluck

Data is now at the core of any modern business. Even Artificial Intelligence is powered by Big Data, highlighting the importance of wasting not a single of drop of what is collected. What is important for businesses to thrive by using data is their capacity to gather it from a variety of sources, collate and source what they have they have been able to collect. With this, business gain invaluable insight that guides their business strategies and decisions. 

With technology being ingrained in business practices, any type or size of commercial entity has access to granular and rich data. These reflect their activities but also customers and other business relationships. Even though many tools exist today to effectively manage all of this information, the sheer mass of what can be obtained can be a challenge both in terms of capacity and cost. Indeed, data usage is expected to surpass 274.3 billion by 2022 globally, with 1.7 megabytes of information per second generated per individual. This explains many businesses may end up making mistakes when dealing with Big Data. 

Youpal Group’s Youdata Team Leader Apostolis Agatzopoulos says: “Companies that have gathered their data, even in an unstructured format, will benefit greatly by performing big data analytics. Experts can apply these methods to give insights, recognise patterns and transform otherwise incoherent data into useful information. Companies that do not gather data can also hire experts to create what we call data lakes (for raw data) or data warehouses (for structured data) that allow them to start storing all data for future use. I believe the next decade will be a crucial juncture that will highlight the businesses that make use of their data in an efficient and smart way that will allow them to increase their revenues and improve their marketing strategies.”

Here are some things to consider to avoid making Big Data mistakes.

  1. Small steps: baby steps pave the way to giant leaps. Begin collecting your data in small quantities so that you can scale up to more colossal collections. 
  2. Security first: never compromise on security. Ensure you have an all-inclusive, unified system for your big-data security. 
  3. Health and skills: your company has a unit that oversees your big-date hygiene. Your data management tea has to be responsible to keep your data up to date. It also has to make sure all staff are properly trained and skilled to manipulate it.
  4. Compartmentalise: Data is like a big jigsaw puzzle. It will be easier to handle if you were to consider it piece by piece, that is in segments. Therefore make sure you break down your data in corresponding sections.
  5. Timely use: there is no point collecting huge amounts of date for silo meditation. If your data goes dormant, you are missing out on important information and insights which could be vital to your business.
  6. Cut your coat according to your cloth: use tools that correspond to your needs. Big-data handling can be expensive if you are more focused on buying costly software to handle it rather than going through a staggered process.

As Big Data becomes the crucial to businesses in all industries and of all sizes, opportunities will also give rise to challenges in managing this resource efficiently. Data volumes will continue increasing and migrating to the cloud. Predictions suggest the global data sphere will attain 175 zettabytes in 2025, thus highlighting the importance of not passing up this next step of digital evolution. However, the idea is not only to do so and be part of the evolution, but to do it right.

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