Whether you are a startup, an SME, or a large enterprise, data is always at the epicenter of any organization’s success. Everything you do, the decisions should be data driven rather than based on ‘gut feeling’. Data is indeed very helpful while making decisions, but with accelerated digitization of the world, organizations are swamped with massive amounts of data.
Today, it has become more crucial than ever, to understand that not all data is useful. Data is in abundance yes, but that is not solely enough to derive smart decisions. The art of swimming through that load of data and finding the right information to base your decisions on, is the real challenge for many. A lot of companies waste their time and resources, trying to make sense of every type and kind of data they receive. Not all the data, is supposed to make sense and provide insights. We occasionally collect data without even knowing why and what. Hence, lets try to understand how to use your data effectively and spend your time, money, and resources efficiently.
When To Use Data
Data is used in multiple settings within an organization. Analysts within a company strives to use data for business intelligence and derive useful insights. Every department uses data for different uses. Lets take a quick look
The finance department uses data such as cash flows, balance sheets, income statements, assets, liabilities and other forms of financial data. They use the data to analyze risk, lower cost, and make strategies to increase revenues.
In marketing, data is used to analyze consumer behavior such as their, buying pattern, seasonality, trends, measuring performance of marketing campaigns etc.
HR uses data for HR data analytics in order to improve recruitment, training, development, performance, and compensation processes. By using relevant data, HR managers can make smarter decisions to meet organizational goals.
Challenges In Using The Data Effectively.
- When Data is late
Businesses have gotten too fast-paced in today’s day & age. With high competition, companies are moving towards real-time data analytics to make decisions quicker. In such an environment if the data collection or extraction process gets delayed, it could cause potential loss to the company. Hence, timely data collection is crucial for effective data usage.
- Irrelevant data:
With a lot of data coming in, a lot of inconsistent and irrelevant data is also collected. It slows down the data analysis we first must filter out the irrelevant data.
A lot of data is stored in PDF file format as they are widely used across organizations. However, extracting data from PDF files to excel is not an easy job. A lot of manual effort goes in it as there are numerous PDF files with useful information trapped inside. Since the process is done manually, there are chances of human errors in data extraction process causing the data to be unreliable and flawed. This hinders the effectiveness of the data as well as the overall data management process.
What To Do?
To avoid these problems, there are now tools in the market that effective use of data easier. These tools are called data scraping tools. These tools allow us to extract data from unstructured file formats by using data models, that can be replicated for files of similar format. This automates the process of data extraction, making the process fast. Hence it prevents data delays, increasing efficiency thereby.
Moreover, they allow the user to build their custom data models and select precisely which information they want to extract from a document. This allows automated data extraction while keeping the data relevancy in check. These tools also come with ETL functionality where you can apply data quality rules to make sure the data is reliable without any duplication or erroneous entries.
Using data effectively is a challenge every company faces and its crucial to be aware about productivity tools in the market that can boost your processes. Data scraping tools are one of those crucial tools that a business must have.