Since data has become the fuel of machine learning and artificial intelligence, most businesses have become data-intensive. While most data providers and tools can assist companies in obtaining data in large quantities, they do not assure data quality. Therefore, organizations must realize the importance of data cleansing to eradicate errors in datasets. Leveraging the expertise of data cleansing companies is the best way to remove and fix corrupt, poorly formatted, inaccurate, erroneous, duplicate, and incomplete data points within datasets.
Even
the most sophisticated algorithms are beaten by high-quality data. You will get
misleading results without clean data, jeopardizing your decision-making
processes.
According to Gartner’s research, Measuring the
Business Value of Data Quality, 40% of companies fail to meet their goals due
to poor data quality.
So,
it has become a necessity to have a solid data management strategy.
While deleting unnecessary
data is vital, the ultimate purpose of data cleansing is to make data
as accurate as possible. With this process, you can make datasets
as accurate as possible. It helps correct spelling and syntax
errors, identifies and deletes duplicate data points, and
fills mislabeled or empty fields.
Importance Of Data Cleansing
According to a Gartner report, companies believe
that poor data costs them roughly $13 million yearly. More
importantly, the research company discovered that 60% of organizations do not
know how much incorrect data costs them since they do not track the effect.
It
is believed that when it comes to data, your insights and analyses are only as
good as the data you use, which directly means junk data equals rubbish
analysis. Data cleaning, also known as data cleansing and scrubbing, is
critical for your business if you want to foster a culture of quality data
decision-making.
The
datasets are more likely to be erroneous, disorganized, and incomplete if it is
not cleaned beforehand. As a result, data analysis will be more difficult,
unclear, and inaccurate – so will the decision based on that data analysis. To
avoid the effects of poor data on your business, cleanse datasets as soon as
you collect them. Not only will this reduce mistakes, but it will also reduce
your staff’s frustration, boost productivity, and improve data analysis and
decision-making.
How To Cleanse Data?
Data
cleansing is the process of preparing data for analysis by weeding out
extraneous or erroneous information. Going through zillions of data points
manually for cleansing is a time taking and error-prone process. So, data
cleaning technologies are crucial in making data ready for usage.
Data
cleansing tools improve the quality, applicability, and value of your data by
eliminating errors, reducing inconsistencies, and removing duplicates. This allows
organizations to trust their data, make sound decisions, and provide better
customer experiences. Data cleaning tools, also known as data scrubbing or data
cleaning tools, find and eliminate incorrect or unnecessary data points and
make the database precise for analysis. Employing automation to cleanse your
data means that your talented resources can focus on what they do best while
the tool takes care of the rest.
Many data
cleansing service providers globally offer hassle-free data cleansing
services to those who don’t have the time or resources to use a tool for making
datasets relevant for quick and precise analysis. Choosing a tool is always a
more cost-effective and hassle-free option for data cleansing. With a data
cleaning tool, things that can be easily removed from datasets to make them
more relevant for analysis are –
·
Missing
fields
·
Outdated
information
·
Data
entered in the wrong field
·
Duplicate
entries
·
Misspellings,
typing errors, spelling variations
·
And
other flaws
What Features To Look For When
Choosing The Best Data Cleansing Tool?
If
you don’t trust the data used in your daily work, it’s high time you start
cleaning it using a cutting-edge tool with the power of AI.
An
AI-powered tool delivers a whole host of specific benefits. It provides better
quality data that is accurate, valid, properly formatted, and complete in a
timely manner. Even top data cleansing companies today employ
data cleansers to weed out erroneous, unstructured data from the
datasets.
But
the question is, what features to look for when finding the right tool to get
the work done? Here is the list of the top 7 features that the best
data cleansing software must have.
1. Data Profiling
Data profiling is the process of
evaluating, analyzing, and synthesizing data into meaningful summaries.
The approach produces a high-level overview that can be used
to identify data quality concerns, hazards, and general trends. It
translates numbers into terms and generates key insights that ordinary people
can understand and may subsequently use to their advantage. Charts.
Trends. Statistics. Data profiling allows for the creation of bird’s-eye
summaries of tabular files. It gives extensive information and descriptive
statistics for each dataset variable. Data profiling and cleansing features,
which can automate metadata identification and provide clear visibility into
the source data to detect any anomalies, should be included in an end-to-end
data cleansing solution.
2. Excellent Connectivity
A
data cleansing tool should handle standard source data formats and destination
data structures, such as XML, JSON, and EDI. Thanks to connectivity to popular
destination formats, you can export clean data to various destinations,
including Oracle, SQL Server, PostgreSQL, and BI applications like Tableau and
PowerBI. So, choose the best data cleansing software that
offers excellent connectivity. This will help your company to gain faster
access to high-quality data for rapid decision-making. Being data-driven in
today’s world has become necessary since it helps businesses to be
profitable.
The data-driven
company is not only 23 times more likely to attract consumers, but they are
also six times more likely to retain customers and 19 times more likely to be
profitable, states
McKinsey Global Institute.
3. Data Mapping
The best data cleansing software should
have a data mapping feature since it bridges the gap between two systems or
data models so that when data is transported from one location to another, it
is accurate and usable at the same time. Each of the best data
cleansing companies uses easy data mapping tools. The usability of a data
cleansing tool is improved by the data mapping feature. It’s critical
to correctly map or match data from source to transformation and then to the
destination to ensure that your data is cleansed accurately. Such functionality
can be supported by tools with a code-free, drag-and-drop graphical user
interface. Always check the data mapping features when you choose the data
cleansing tool.
4. Quality Checks
47% of new data collected by companies has one or
more critical mistakes.
When collected data fails to match the
company’s standards for accuracy, validity, completeness, and consistency, it
can seriously affect customer service, staff productivity, and critical
strategy-making. Data used for business purposes should have accuracy,
completeness, reasonability, timeliness, uniqueness/deduplication, validity,
and accessibility. So when you choose the data cleansing tool, make sure it
offers advanced profiling and cleansing capabilities along with data
transformation functionality. Many data cleansing companies and data
cleansing service providers use such advanced data cleaning tools to
deliver accurate data for business intelligence.
5. Friendly Interface
Choose a data cleansing tool that has a highly
intuitive and friendly user interface. It should be easy to use and yet
powerful to handle large-scale data cleaning. An ideal data cleansing tool
should be used by anyone, not just IT people. When you use a data cleansing
tool with a friendly user interface, you don’t need
any expertise or expert IT professionals to operate it. The
data cleansing process also becomes super fast with the best
data cleansing software having a simple and friendly UI.
5
Benefits Of Automating The Data Cleansing
Process For Your Company
According to Kissmetrics, companies might lose up
to 20% of their revenue due to poor data quality.
Cleansing
data and making it usable has become a necessity today. Data cleansing is frequently
a task of data scientists and business analysts, whether they are new to the
field or have been doing it for years. It isn’t the most enjoyable aspect of
the work, but ensuring that your data is useful and accurate in the long run is
required.
If
data errors and the process of their eradication creeps you out, it’s best to
put data cleansing on auto-pilot mode. Automation eliminates the need to
manually search through each data piece to identify problems. Automating the
data cleansing process has some unexpected benefits that only data
cleansing companies have considered. And it’s time for you to automate
your data cleansing process and enjoy its benefits like –
1. Increased Productivity
78% of business leaders agree that automating
workplace tasks boosts all stakeholders’ productivity.
Automation impacts your business
operations and workflow in a positive way. Discussing data cleansing
automation, it eliminates the need to manually comb through data pieces to
identify errors, duplicates, and other flaws. Instead of spending hours
manually altering data or doing it in Excel, use data cleansing tools. They
will perform the heavy lifting for you. More and more datasets will be cleansed
when you put the process on autopilot mode.
2. Saved Time
Imagine
yourself cleaning datasets one by one. Isn’t it scary? If you clean every piece
of data one by one from your large datasets, it is going to take an
eternity.
According to MIT Sloan research, employees squander
over half of their time doing mundane data quality activities.
Automating the process saves you a lot
of time which you can simply use on other important tasks. The most
significant benefit of automation is the ability to do repeated tasks fast and
without mistakes. You’ll save not only a lot of time but also eliminate
time-consuming tasks like exporting and importing tables to keep your system up
to date.
3. Reduced Cost
Automating
data cleansing reduces the need for a specialist data cleansing team. There is
no need to spend excessive money on training staff and providing them with a
well-equipped working space.
74% of surveyed marketers believe that business
owners and marketers use automation to save time and money.
With a little guidance, a non-tech
person can easily use a data cleansing tool. You are going to reduce the cost
of data cleansing by introducing automation.
4. Improved Accuracy
Accurate data is critical to the
success of any business and project. However, checking for data accuracy
manually can be difficult and time-consuming. That is why automation is so
beneficial. You’ll never have to worry about manually checking for
mistakes or dealing with the intricacies of your database again with automated
data management.
5. Improved Focus On Core Tasks
The
data cleansing process can be effectively automated using a cutting-edge tool.
Users get more time to focus on strategic business-related core activities,
while automation software takes care of repetitive tasks.
In fact, 85% of business leaders believe that
automation improves their focus on strategic goals.
Manual
data cleansing is a time-consuming and tedious procedure that might take days
to complete. That is why it is critical to automate it. While maintaining data
quality is a problem for every new organization, you can avoid being lost at
sea with the correct data cleansing methods and technologies.
If you don’t have time to clean the
datasets, even using a tool, you can simply choose a data cleansing company.
Many data cleansing service providers outsource data
cleansing services to their customers and make their valuable datasets
error-free and ready to use for instant analysis. They reduce the hassle of
finding an ideal tool for data cleansing.
Choose A Team, Not Just A Tool
When
you’re searching for a solution to clean up your entire data system, you’re
looking for more than simply a tool. You’re looking for an expert team to help
you solve your data problems. Why? Because cleaning big data systems requires
more than merely comparing rows and columns to find problems. It is a business
practice that necessitates a full grasp of your company’s surroundings,
difficulties, and data objectives. Only an expert team capable of doing
everything can help you get the most out of the tool.
One
of the best data cleansing companies that you can choose for
adding accuracy to your datasets is Outsource BigData. We have trained
professionals to provide cutting-edge data cleansing services to customers
having large-scale databases. Along with data management, collection, and cleansing
services, we offer our customers round-the-clock IT support.
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