data pain points

Top 8 Data Pain Points — and How Kloudio Helps [2021]

The world of technology is thriving, and there is much to consider for storing, using, and analyzing your business data. Business leaders, operational teams, and developers often rely on these valuable data assets to make meaningful decisions to further their business goals.

However, today’s plethora of data leads to a number of pain points that both data analysts and business users face. Let’s unpack some of these data pain points and explore how a tool like Kloudio can help.

Data Pain Points for Data Analysts

1. Data Trapped in Silos

Data is a dynamic entity and is often spread across different verticals within an organization, making data availability an ongoing challenge. A data analyst is expected to consolidate such data in order to drive meaningful analysis.

Most data is spread across repositories — some within silos, and some not accessible at all. In fact, some data may not be digitized either, which can post another set of problems for the end-user.

For example, a data analyst who’s looking to mine insights from customer behavior data may find data for different customer types trapped in separate stand-alone databases. Moreover, some information might only be available in paper feedback forms at the store.

A typical mix of data includes structured data (in-house databases) along with unstructured data from a variety of sources, like emails, system logs, and social media.

How Kloudio Helps Overcome Data Access Issues

Kloudio can access a series of data sources and repositories, all through a single platform. Imagine how flexible your reporting would become when you are able to consolidate data by connecting to different platforms with minimal effort.

Rest assured, data consolidation continues to be one of the strongest fortes of Kloudio. We specialize in reducing the time and effort taken to access data from different data warehouses, data lakes, and much more.

2. Handling a Lot of Data Quickly and Accurately

When a quintillion bytes of data gets generated every day from sources like websites, social platforms, smartphones, online transactions, and sales points, companies tend to feel overloaded.

Even the best team of data analysts, with all their tools and resources at their disposal, can’t successfully simplify and process this data within a stipulated period. Hence, processing and analyzing data in an economical manner becomes a challenge for enterprises and their analysts.

For example, Apache Hadoop is one of the most widely used tools for analyzing large chunks of data. While one of its functions, MapReduce, can break a whole volume of data into smaller and processable fragments, the tool inherently struggles with real-time resource allocation, data sharing, scheduling, and cluster management.

Processing unstructured data is a crucial part of data analysis, and this step takes up a majority of a data analyst’s time, effort, and resources. For any successful, conclusive, and extensive data analysis, it’s essential to understand how data is generated in a step-by-step manner.

How Kloudio Helps Manage Large Repositories of Data

Kloudio was created to help end-users manage large quantities of data so that you never have to feel overwhelmed by the volumes of data available for analysis. All you have to do is connect to your data repository, and let Kloudio do the work for you. 

All data will be efficiently analyzed, and you would have a well-structured report available for analysis, in a matter of minutes. 

3. Working with Raw Data

Raw data is a form of data that is yet to be processed. Such data includes many complex and unknown information fragments, which can be with or without correct headers and data. These pieces need to go through a cleaning process, in order to make them usable.

The cleaning process is as follows:

  • Technically correct data: After a basic cleaning process, analysts can get their hands on technically correct data with understandable encoding and proper headers.
  • Consistent data: This data type is readily usable for all kinds of analysis. Hence, this is where the actual analysis part starts.
  • Statistically accurate results: Analysts get the statistics, and these results are ready to be presented for interpretation.
  • Successfully processed data: It’s the end product and can be saved for future analysis as per different parameters.

Typically, most analysts spend their time cleaning and processing raw data, making the process less efficient and labor-intensive. This time, which should be spent in analyzing data, is a by-product of the data preparation process, and costs organizations a lot of valuable time, effort, and resources.

More often than not, organizations don’t possess the right tools for performing this task efficiently, which makes the process cumbersome, ill-managed, and unregulated.

4. Varied Data Interpretation

As humans, we tend to have varying perspectives on data. For this very reason, there might be gaps between one person’s analysis and another. The changing levels of information perceptions and analysis can prove fatal for a business, as everything works in the way critical numbers are derived.

In this regard, it is important to have everyone working on the same platform, so that there is an alignment in how different data analysts are analyzing and interpreting their data assets. This is hardly the case with present-day organizations; since tons and tons of data is churned out on a daily basis, it is often difficult for analysts to realize the true potential of their analysis and how one small error can have a major impact.

How Kloudio Helps Overcome Data Interpretation Issues

With Kloudio, you can automate the daily data downloads, interpretation, and analysis procedures, so that every data source is considered. All your data analysts can work on the same data assets, reports, and graphical representations, which reduces the level of complexity and challenges of multiple interpretations amongst users.

5. Accessing and Analyzing Old Data

Making decisions based on stale data is one of the biggest hindrances to effective data analytics, which causes a lot of problems in the long run.

After all, using historic data to perform predictive analytics is one thing, but reporting on stale data for day-to-day decisions can directly impact your bottom line. Many organizations find themselves reporting on old data as they lack the bandwidth and the technology to perform regular, fresh reporting.

How Kloudio Helps Overcome Data Reporting Issues

Kloudio helps automate some of the basic pain areas around data extraction, transformation, reporting, and scheduling. Imagine the freshness of your daily reports, as an automated database provides you with a fresh set of reports, with the latest numbers, at set intervals throughout the day.

6. Inconsistent Data Quality

As a data analyst, data quality continues to take precedence over all other issues. Despite this, there is always a rise and fall in the levels of data quality, especially if there is a level of human intervention involved.

Having said that, automation does not come cheap, which puts it on the back burner for a lot of organizations. However, what many business leaders fail to realize is the importance of sustainability in data analytics, and the need to access consistent, fool-proof data, which can help make invaluable decisions.

How Kloudio Helps Overcome Data Quality Issues

If you are looking for a platform that can reduce data quality issues by inputting data automation within reporting standards, then Kloudio is your go-to platform. From automated data collection to reporting, to visualization, and report scheduling, there is a little bit of everything Kloudio can do for your business, at affordable costs.

Data Pain Points for Business Users

Business users have an unending dependency on data analysts to pull data and drive insights through reports and visualization. But the list of problems does not end here; there are a few things business users consider to be their pain areas, which are addressed below.

7. Lack of Technical Skills

Business users often lack the necessary skill sets to pull data from data lakes, warehouses, and other repositories. When you have data resources, you need technical skills to readily pull data into usable formats, which can help in making meaningful decisions for the future.

However, business analysts and business users might often face challenges pulling data directly from such data sources, especially when the imminent skill sets include the likes of SQL and other database query management tools.

How Kloudio Helps Overcome a Lack of Technical Skills

Kloudio allows technical users to create and store SQL procedures within Google Sheets so that non-technical users don’t have to worry about writing endless queries for fetching data. By running pre-written codes, business users can efficiently pull the required data into their reports, and get real-time data for making decisions.

8. Using Multiple Platforms for Data Collaboration

Business users, like data analysts, might find themselves running from one platform to another, trying to fetch the required data for visualization and data reporting. However, this does not have to be the case specifically, as there is always an option to have pre-configured reporting in place, which would collaborate with different platforms and fetch data in one go, as per set timelines.

How Kloudio Helps Overcome the Use of Multiple Platforms for Data Collaboration

Imagine how well you can access a series of platforms from one platform. That’s right; this is the beauty of Kloudio’s tools. Enterprises can store different forms of data in varied platforms like RedShift, Dropbox, Salesforce, Jira, etc. 

Kloudio’s integrated platform can connect to multiple sources, and create a single, consolidated repository for the end-users to prepare their reports on a regular basis.

What data pains are you wrangling with?

Kloudio’s futuristic approach towards automation, data consolidation, report scheduling, and visualization is designed for business growth. Organizations often face major data-related challenges, which can create obstacles in the path to success.

Kloudio’s features are one of a kind, and the organization offers a unique approach to solving all data-related problems for various kinds of enterprises. If you are keen to try out their products, create your free Kloudio account. and get a feel of their services for yourself.

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