Lately, data has become central when business owners want to make crucial decisions. The volumes of data produced and stored have significantly increased too. The stored data can be located remotely in different places, causing management challenges.
Dealing with data performance degradation
Each day, business operations increase the volume of data
generated. In the first few thousand terabytes, there is no performance issue
experienced. The speed of data retrieval and storage goes smoothly, as
expected.
As volumes increase to millions of terabytes, speed begins to
slow. Anytime a request is made for accessing the data store, the speed of
processing becomes slower all the time. Data performance degradation affects a
lot of other things in the daily running of a business.
One of the techniques business owners use to manage data
processing speed challenges is caching. The technique helps store frequently accessed data in the
memory without affecting speed due to the limitation of available space.
Handling big volumes of data
Out of the approximately 2.5 quintillions of data generated
daily, the big chunk of it comes from businesses. This leaves businesses with a
big challenge of storing and retrieving the data. There are not enough hard
disks that can be enough to store such volumes of data.
Due to this challenge, some of the businesses are planning digital transformation to help them overhaul their
data storage, retrieval, and processing solutions. Some are opting for RAM
storage, data warehouses, cloud, or data lake storage, depending on the size of
the business.
Dealing with multiple data storage locations
When the volume of data increases exponentially, there is a need
to store it in different locations. Larger businesses may provide a different
data storage solution for each of its departments. By obtaining multiple
storages, the business owner solves one part of the problem.
They have to create another way to help them identify each
portion of data and consolidate it in the main data platform. That means all
the data in multiple datastores must be linked to allow access from one
platform.
At this point, business owners require one or more data
integration technologies to link the various data stores. Some of the
technologies used are enterprise data replication, enterprise information
integration, extract, transform, load.
Data security challenges
The data that a business collects comes from multiple sources.
Some of it comes from marketing platforms, social media platforms, blogs,
websites, etc. The security of each source cannot be trusted.
The biggest challenge comes when the data has to be stored in
one place within the data stores. If some of the data is comprised of malware or spyware codes, it can compromise the
entire data.
This calls for business owners to have strict data security best
practices to help keep the datastores secure. The IT department could be tasked
with identifying and classifying sensitive data. The crucial data can be stored
separately and more strict security measures implemented. The management may
also implement rules and guidelines for accessing data.
Maintaining consistent data quality
Although a business has the advantage of accessing and
collecting large volumes of data, not all of it is beneficial. When collecting
it from various sources, it might be difficult to tell if the data is useful or
not.
When it arrives in the business datastores, the unwanted data
will only occupy space but will not add value to the business. It must be
sorted out so that the unimportant data is removed to give space to useful
data.
Most businesses store all the data as it is. The non-useful data
compromises the quality of the useful data. When it is all used during
analysis, the results obtained will be compromised. The business management
will not make beneficial decisions for the company.
Lack of proper data skills
Different technologies are growing faster. Business owners, on
the other hand, seem to be slower in catching up with the current technology
trends. The business might have all the data it requires for growth but lack
the right skills to handle it.
Some of the skills required are skills to ensure data integrity
and data navigation. There is a need to have skilled data analysts, database
designers and planners, and data management skills. Some business owners are
currently spending a lot of money to train data professionals. Others are
paying experts to help them hire the right talents with data management
skills.
Dealing with real-time data access
For a business owner to benefit from the advantages of big data,
fast analysis is required. Historical data found in the business databases may
not help it make decisions. Historical data could be any data stored a few
hours ago to several weeks ago.
Businesses need to process the data the moment they access it
from multiple sources. When it is still fresh, this is the time when the
business will benefit most from the data. Despite this benefit, most businesses
lack the right capacity or technology to help them process the data in real
time.
Future data management plans
Daily, the amount of data generated in a business increases.
Although the volumes of data keep growing, the available storage might remain
constant. Eventually, the space will fill and the business is left with limited
options.
They have to either delete older data to create space for fresh
data or upgrade their storage. If the business is used to processing a million
terabytes of data, soon it will have 10 million, which will keep growing to
several hundreds of millions.
One of the biggest challenges many businesses are facing today
is having elaborate plans for future data management. The management must put
in place measures that will provide uninterrupted storage solutions. The plans
should keep in mind the following main points.
●
Handling the growing data volumes
●
Dealing with issues of speed
●
Segmenting different data
varieties
●
Dealing with data veracity
●
Getting value from data
