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Effective Data Insights — A Game Changer for Businesses

Data insights are crucial for businesses to make informed decisions and remain competitive in the ever-evolving market. With the increase in the volume, variety, and velocity of data, it has become necessary for organizations to have the capability to analyze data and derive insights that help them make data-driven decisions. This article will explore the importance of data insights for businesses, steps to achieving effective data insights, best practices, tools, challenges, and future of data insights.

Introduction to Data Insights

According to KnowledgeHound, Data insights refer to the process of analyzing and interpreting data to extract meaningful information that can be used to make informed decisions.

It involves using various tools and techniques to identify patterns, trends, and relationships in data. There are many resources available for beginners who want to learn about data analytics, including online courses and guides.

These resources cover topics such as the role of a data analyst, tools used in data analysis, and the entire data analysis process. With the increasing demand for professionals with skills in data analytics, learning this field can be a great way to kickstart a career.

Importance of Data Insights for Businesses

Data insights are crucial for businesses as they provide valuable information that can be used to make informed decisions. By analyzing customer data from various channels, businesses can gain insights into customer behavior and preferences, which can help them provide a more personalized experience.

Historical data analysis can also help businesses anticipate fluctuations in consumer demand and make better business decisions. Companies that embrace data analytics initiatives can experience significant financial returns. Data analytics helps businesses optimize their performance by identifying areas for improvement and making strategic investments.

Implementing data analytics into the business model means companies can stay competitive in today’s market by making informed decisions based on real-time data.

Steps to Achieving Effective Data Insights

Achieving effective data insights involves several steps.

Firstly, it is important to align the data strategy with the business strategy and identify relevant business drivers that could be positively impacted by data and analytics.

Secondly, organizations need to implement processes such as data cataloging and governance and embrace culture changes to achieve effective analytics programs.

Thirdly, businesses should use deep learning to get value from unstructured data.

Finally, carrying out various analyses on the data is essential to obtain insights. The four types of data analysis include descriptive, diagnostic, predictive, and prescriptive analysis.

By following these steps, businesses can turn their data into actionable insights that can be used to make informed decisions.

Best Practices for Data Insights

To achieve the best results from data insights, businesses should follow some best practices.

It is important to define business objectives and identify the key performance indicators that will be used to measure success.

Building high-performance analytics teams and promoting data literacy within the organization can help ensure that everyone understands how to use data effectively.

Collecting, storing, and organizing data correctly is essential for accurate analysis.

Segmenting the audience can help businesses gain a better understanding of their customers’ behavior and preferences.

Using data storytelling can help promote insights by making complex data more accessible and understandable.

Utilizing new infrastructure technology and more advanced analytics can help businesses stay ahead of the competition.

By following these best practices, businesses can turn their data into actionable insights that drive growth and success.

Tools for Data Insights

There are many tools available for data insights that businesses can use to analyze and interpret their data. Some of the most widely used business analytics tools include Microsoft Power BI, Tableau, Qlik Sense, Excel and KnowledgeHound.

These tools are designed to help businesses visualize and analyze their data to gain insights into customer behavior, market trends, and other key metrics. These tools offer a range of features such as data visualization, predictive modeling, machine learning algorithms, and more.

By using these tools effectively, businesses can turn their data into actionable insights that drive growth and success.

Challenges in Data Insights

There are several challenges that businesses face when it comes to data insights.

Managing vast amounts of data can be a challenge, as it requires the right tools and techniques to analyze and interpret the data effectively.

Seelecting the right analytics tool can be difficult, as there are many options available and each has its own strengths and weaknesses.

Data visualization can be challenging, as it requires businesses to present complex data in a way that is easy to understand.

Dealing with data from multiple sources can be a challenge, as it requires businesses to integrate different types of data into a single system.

Low-quality data can also pose a challenge, as it can lead to inaccurate insights and decisions.

Other challenges include cultural dynamics within the organization, inaccessible data, lack of system integration, excessive costs, complexity and skills gaps.

By addressing these challenges effectively through proper planning and implementation of best practices for data insights, businesses can turn their data into actionable insights that drive growth and success.

Future of Data Insights

The future of data insights is promising, with several trends emerging that are expected to shape the industry in the coming years.

Businesses are expected to emphasize business intelligence, edge data, and cloud-native technologies.

Data democratization, artificial intelligence, and real-time data analytics are expected to become more prevalent.

Adaptive AI systems and metadata-driven data fabric are also expected to gain traction.

Real-time automated decision making and no-code solutions are also predicted to be important trends in the future of data insights.

Data quality and observability will continue to be important factors in ensuring accurate insights from data analysis.

By staying up-to-date with these trends and adopting new technologies and techniques as they emerge, businesses can stay ahead of the competition and turn their data into actionable insights that drive growth and success.

Also Read: Different Types of Survey Data Collection Methods You Should Know

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In this digital world, companies rely on survey data to gather information about their targeted audience and their preferences. Businesses employ different methods to collect the survey data and analyze it. There are various mediums used to collect opinions and feedback from customers. While conducting a survey, researchers often choose multiple sources to collect data. KnowledgeHound shares the different methods used to collect the data.,,Learn more

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Different Types of Survey Data Collection Methods You Should Know

In this digital world, companies rely on survey data to gather information about their targeted audience and their preferences. Businesses employ different methods to collect the survey data and analyze it.

According to KnowledgeHound, there are various mediums used to collect opinions and feedback from customers. While conducting a survey, researchers often choose multiple sources to collect data. Today we are going to talk about the different methods used to collect the data.

Survey Data Collection Methods

Over the years, the methods used to collect data have evolved owing to changes in technology. While each survey data collection method comes with its pros and cons, you can choose a method based on your business needs.

· Telephonic Survey

If you are a small business, this is the best bet to collect survey data. These surveys require very less amount of investment as compared to other survey data collection methods. Moreover, getting in touch with your potential customers over the phone requires less effort and manpower than going around the town for a face-to-face surveys.

Companies who are looking forward to understanding their customers purchasing decisions often conduct this type of survey to collect data about their customer’s purchasing experience.

· Online Survey

One of the most cost-effective survey data collection methods, online surveys often help companies to reach a large number of people in contrast to other channels. Moreover, in case you want to ask your customers a group of questions, online surveys are more effective than telephonic or face-to-face surveys.

One of the best examples of an online survey is an online shopping website using the online survey to collect customer satisfaction metrics after browsing the website and completing the purchase.

Online surveys are secure to conduct and are quite useful in today’s global crisis time.

· Paper Survey

For decades, paper surveys have been employed by businesses to collect information. This is an age-old method of data collection before laptops, tablets, and computers were common thing. This collection method uses pen and paper to collect survey data and often strengthens the validity of the responses.

Fast food chains use this survey data collection method to collect feedback and improve their business. They ask their guests about their dining experience and based on the responses choose to alter their services.

· Face-to-face Survey

While gaining information from your customers via face-to-face mediums is more effective than other mediums, it can be time-consuming and expensive. Also, respondents often tend to trust the surveyors more in face-to-face surveys and offer honest opinions.

This is a great method of collecting survey data if there are sensitive topics involved in the discussion. Moreover, the researchers must be trained to gain access to accurate information.

One of the best examples of face-to-face survey data collection methods is a job evaluation survey conducted between the HR and employee. This method works best because the collected information will be accurate and the HR can easily ask “n” number of questions to the candidate.

It is pointless to conduct a survey without having access to the resultant data. Thus, make sure whenever you are conducting a survey, you have access to its analytics.

Also Read — Structured Data — What Is It and How It Differ From Unstructured Data?

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It is important for businesses to manage their data effectively. What is the first thing that comes to your mind when you read “business data”? You instantly think of spreadsheets with names and numbers. This is what is known as structured data. But did you know, only 20% of the data is considered structured? The rest of it is stored as unstructured data...Learn more

For more information, visit the KnowledgeHound website.

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Structured Data – What Is It and How It Differ From Unstructured Data?

A widely misunderstood, yet fundamental building block of the information economy, structured data refers to the method of creating, publishing, and maintaining information. In simple words, structured data is defined as information that is optimized and can easily be read by a computer.

Entrepreneurs are using data to stay ahead of the game. They are using data to understand current trends, look out for new opportunities, and streamline their work. Businesses often hold a mounting volume of data which helps them understand their customers better. This in turn helps them make informed business decisions.

However, it is important for businesses to manage their data effectively. What is the first thing that comes to your mind when you read “business data”? You instantly think of spreadsheets with names and numbers. This is what is known as structured data. But did you know, only 20% of the data is considered structured? The rest of it is stored as unstructured data.

What Is Structured Data?

According to KnowledgeHound, when data is formatted in a way that is easy to read and understand, it is considered structured data. Traditionally, data was often generated to fit in a table format so that it becomes easy to analyze.

Some common examples of structured data are SQL databases or Excel CSV files. Since the columns and rows are labeled, it becomes easy to aggregate data from multiple sources and analyze it.

While structured data make things easier, in some scenarios, it can pose limitations for evolving businesses. By only considering structured data, you may just look into a part of the story that the data is able to reveal.

What Is Unstructured Data?

As the name suggests, unstructured data is any form of data that is stored in a native form instead of standardized spreadsheets or predefined models. Unstandardized data often contains more text than figures or numbers, making it difficult to standardize it.

Example of unstructured data includes content from social media posts, emails, chat records, and web content. Unstructured data also contact formats beyond texts such as video recordings, audio recordings, scientific data, photos, and more.

Unstructured data can be useful for businesses and help make informed decisions only if it is properly leveraged. However, if unstructured data is stored in NoSQL database or data lakes, it can quickly become a potential risk for the organization.

What Is Semi-structured Data?

A combination of both, structured data and unstructured data elements are known as semi-structured data. However, it often falls under the unstructured data umbrella. While some parts of semi-structured data are readable and easy to analyze, those elements do not provide the full value.

HTML code is the best example of semi-structured data. While it is organized in a structured way, HTML code contains defined tags and elements that often pose a challenge for the database to make sense of it.

Structured and unstructured data play an important role in business. While companies have leveraged structured data, they are looking into tools to analyze their structure and unstructured data together.

Also Read — Best Data Visualization Tools To Look Out For In 2023

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According to a report by Fortune Business Insights, the global data visualization market stood at USD 8.85 billion in 2019 and is projected to reach USD 19.20 billion by 2027, exhibiting a CAGR of 10.2% during the forecast period. The increasing use of the internet, smartphones, cloud computing technologies, advancements in machine learning, and the rising use of the Internet of Things are the driving factors behind the increase of the global data visualization market...Read more

For more updates, visit the KnowledgeHound website.

[knowledgehound]

Best Data Visualization Tools To Look Out For In 2023 - KnowledgeHound

According to a report by Fortune Business Insights, the global data visualization market stood at USD 8.85 billion in 2019 and is projected to reach USD 19.20 billion by 2027, exhibiting a CAGR of 10.2% during the forecast period.

The increasing use of the internet, smartphones, cloud computing technologies, advancements in machine learning, and the rising use of the Internet of Things are the driving factors behind the increase of the global data visualization market.

What is Data Visualization?

Before we discuss more on the data visualization tool, let’s first get a good understanding of data visualization. What does it mean?

According to KnowledgeHound Data visualization refers to the process of communication and translation of information and data in a visual context. As the name implies, data visualization often employs charts, graphs, bars, and other visual aids to describe the relationship between different types of data.

What are Data Visualization Tools?

Have you heard about Infogram or Google Charts? These are the tools that often support a variety of visual styles and are capable of handling a vast data volume.

Presenting data through visual elements makes it easy to analyze and understand. Here are the top 3 data visualization tools that are known for their incredible performance and impressive usability.

· Tableau

Tableau is one of the most commonly used data visualization tools, trusted by over 57,000 companies. Tableau provides integration for advanced databases, such as Amazon AWS, SAP, Hadoop, and My SQL, and creates graphics and visualizations from ever-evolving datasets often used for machine learning and artificial intelligence.

While tableau offers excellent visualization capabilities and supports connectivity with a wide range of data sources, the pricing is on the higher side. This can be seen as a con by many people.

· Google Charts

Google Charts has been one of the major players in the market space for a long time. Google Charts coded with HTML 5 and SVG have the capability to produce pictorial data and graphical data.

This data visualization tool provides users with unmatched cross-platform compatibility with android and iOS. Google Charts offer a user-friendly platform, is compatible with Google products, and has visually attractive data graphs. It is also easy to integrate the data.

However, it lacks customization abilities and network connectivity which is often required for visualization. Also, there are inadequate demos available on how to use the tool.

· Zoho Reports

Also called Zoho Analytics, Zoho Reports is a data visualization tool that integrates online reporting services with business intelligence. This allows quick creation and sharing of the reports in a few minutes.

This data visualization tool also supports the import of big data from databases and applications. Zoho offers the ability to create reports and modify them effortlessly. It also includes different features such as report sharing and email scheduling. The customer support is amazing.

However, the dashboard can seem confusing when you are dealing with a large volume of data.

While you can easily get your hands on some amazing data visualization tools, make sure to take your time to try out a few tools before settling for the best data visualization tool for your business.

Also Read — What Is Data Management And Is It Really Important?

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Data management refers to collecting, organizing, protecting, and storing the data required by a business to make informed decisions. Data management solutions become a vital part of a business because, in this digital world, companies create and consume data at unprecedented rates...Learn more

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What Is Data Management And Is It Really Important? — KnowledgeHound

Nowadays, companies have access to a humongous amount of data. Businesses use this data to create a foundation to take important business decisions. It is important for businesses to have access to the right data and thus they invest in data management solutions.

What is Data Management?

Data management refers to collecting, organizing, protecting, and storing the data required by a business to make informed decisions. Data management solutions become a vital part of a business because, in this digital world, companies create and consume data at unprecedented rates.

Different Types of Data Management

Data management plays an important role in an organization as it makes essential functions easier and less time-consuming.

Different data management techniques are:

Data preparation — This technique is used to transform raw data into structured data for easy analysis.

Data pipeline — This technique enables the transfer of data from one system to another automatically.

ETLs — The ETLs or Extract, Transform, Load makes it easier to collect data from multiple sources and streamline it into a single source. This system takes in data from one system, processes it, and uploads it into the organization’s data warehouse.

Catalogs — The data catalogs help manage the metadata. The catalogs help create a picture of the data, including a summary of changes and quality while making it easier to find the data.

Data warehouse — This is a place where data from various sources is consolidated and stored for further use.

Data security — Companies use data security to protect the data from getting corrupted or from unauthorized use. CAPTCHA is a perfect example of data security.

Is Data Management Important for your Business?

Data management plays an important role in an organization as it helps to manage the data effectively. With effective data management, people within an organization can easily find and access data to answer their queries.

Here are some benefits of data management solutions for your enterprise.

· Increased Visibility

Data management solutions help increase the visibility of the most important data of your organization. This makes it easier for people within the organization to quickly and confidently find the data they are looking for.

Increased data visibility also allows companies to stay organized and productive while finding data with ease, whenever it is required.

· Reliability

Data management helps eliminate errors by streamlining data. Data management solution establishes processes and policies that can be used to build trust and make the right decisions across the organization. With streamlined and up-to-date data, companies can make effective changes based on customer needs and market changes.

· Scalability

Data management makes it easy for businesses to scale their data effectively and keep it up to date. When it is easy to repeat a process, you can cut back on unnecessary costs of duplication. This saves you time and resources.

Data management makes your business more effective and responsive to your customer’s needs. With proper data management, you get insight that will help you offer more value to your customers and connect better with them.

Having the right data will make it easier to find key business opportunities while increasing your business revenue.

Also Read — KnowledgeHound’s Rapid Reports Continues To Improve!

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KnowledgeHound, the world’s only search-based analytics solution for survey data, announced its most sought-after product release with Rapid Reports earlier this year. Rapid Reports by KnowledgeHound is designed to fit into your existing workflow whether you need full cross tabs or wish to zoom in on a particular visualization of your data...Read more

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KnowledgeHound’s Rapid Reports Continues To Improve!

KnowledgeHound, the world’s only search-based analytics solution for survey data, announced its most sought-after product release with Rapid Reports earlier this year. Rapid Reports by KnowledgeHound is designed to fit into your existing workflow whether you need full cross tabs or wish to zoom in on a particular visualization of your data.

Since then, the feature has been eagerly adopted and is fast becoming the most popular aspect of the software. With a feature as quickly accepted as Rapid Reports comes an influx of feedback from users, to which KnowledgeHound has keenly listened! Now, in large part to this feedback, Rapid Reports boasts of the following features:

Save time by building a segmented report in just a few clicks

Easily analyze entire datasets with robust filtering and cross tabs

Share your findings with a variety of chart styles

[new!] Easily download your report to either Excel or PowerPoint

[new!] See summarized highlights of the most significant findings in every report

[new!] Revisit and edit previously built report for template building and easy tweaks

“I’ve been with KnowledgeHound since the very beginning with our founder, Kristi Zuhlke. We started this company nine years ago working out of a coffee shop and my Chicago studio,” said Joe Razza, founding team member and VP of product & design. “Working faster and more efficiently than the status quo is one of the biggest opportunities we have as a technology. The Product Team has several clients in beta to ensure this meets the day-to-day needs of your key stakeholders. Rapid Reports can be as simple or sophisticated as you need, depending on what you’re looking to understand. Insights teams can analyze dozens of variables in minutes, which is 10x faster than it would take using previous features.”

Users can still leverage Rapid Reports to unlock consumer patterns that they didn’t know existed and ultimately export to a presentation-ready or classic table format. It supports all your unique reporting needs.

“We need to be able to quickly uncover where there are major differences in a study’s responses across demographic variables,” one client said after their beta test of Rapid Reports. “This allows us to do just that.”

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Learn more about KnowledgeHound’s Most Sought-After Product Release With Rapid Reports.

Watch our YouTube video about the launch of Rapid Reports.

About KnowledgeHound

KnowledgeHound is a Chicago-based marketing technology company. Its search-based survey data analysis solution empowers clients to make customer-focused decisions on the fly by maximizing the impact and lifetime value of already expensive and hard-to-leverage survey data. The company is proud to partner with world-class Fortune 500 organizations, transforming and unifying survey data into approachable insights that allow their market research and analytics teams to move at the speed of the business, ensuring their customers stay at the forefront of every business decision while driving efficiencies along the way….Learn more

Also Read - Why You Need Search-Driven Analytics?

[knowledgehound]

KnowledgeHound, the world’s only search-based analytics solution for survey data, announced its most sought-after product release with Rapid Reports earlier this year. Rapid Reports by KnowledgeHound is designed to fit into your existing workflow whether you need full cross tabs or wish to zoom in on a particular visualization of your data.

[knowledgehound]

As the world’s only search-driven survey data analysis solution, Knowledgehound enables Fortune 500 companies to unlock the potential hidden in their survey research.  We exist to help uncover and amplify the critical insights that drive greater audiences, happier customers, and the wins over your competitors that insights teams exist to create...Read more

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Why You Need Search-Driven Analytics? — KnowledgeHound

As the world’s only search-driven survey data analysis solution, Knowledgehound enables Fortune 500 companies to unlock the potential hidden in their survey research. We exist to help uncover and amplify the critical insights that drive greater audiences, happier customers, and the wins over your competitors that insights teams exist to create.

Below are a few of the ways we most commonly help our clients:

1. There’s not enough time in the day

Fear not, KnowledgeHound helps teams reduce the time spent analyzing data by up to 75%. Study up on our $1B pharma client case study.

2. My data is going to waste

We know that all too well… maybe we can help! It’s likely because most of your data is inaccessible to your key stakeholders. Check out this success story on how Fandango transformed into insights explorers.

3. I can’t find the answers I need

Oh no! Help is on the way….. 🏃KnowledgeHound layers the power of search onto an analytics platform built specifically for your survey research. Learn more about how search-driven analytics can unlock powerful outcomes for your business here.

Whether you’re often stuck in Excel building custom tables for a marketing colleague or spending hours crafting a Powerpoint presentation or even answering calls from your agency partners around target messaging, KnowledgeHound makes it insanely easy to find the right insight at the right time to make you look like the rockstar that you are!

Built to ingest, house, and analyze all kinds of respondent-level data, KnowledgeHound is the platform of choice for insights teams that have mountains of consumer data, but need to move quickly when answering critical business questions. Simply connect your favorite DIY survey tools to your account or have your vendor send us your data files, and off to the races you go!

“I immediately saw KnowledgeHound and thought it would make my own life 1000x easier. This stuff takes me hours, days and weeks. It’s a solution that would also help improve synergies across teams. I like the ease-of-use, the interface is very visually appealing and easy to understand. ” — New International CPG Client…..Read more

Also Read: How Danone Changed The Direction Of A $1.4 Billion Line

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Danone was on the verge of deploying a handful of category-level A&U studies that contained a wealth of data related to their consumer’s habits and practices. By opening up the data behind their research for exploration in KnowledgeHound, the team was able to discover new insights that weren’t included in the final reports. This deeper level of exploration led to the discovery of a completely new insight that impacted the future direction of a $1.4 billion product line......Read more

[knowledgehound]

How Danone Changed The Direction Of A $1.4 Billion Line

Situation: Danone was on the verge of deploying a handful of category-level A&U studies that contained a wealth of data related to their consumer’s habits and practices. They felt the traditional method of sharing results via large Powerpoint decks would not be enough to ensure the data behind this foundational research was leveraged in day-to-day decision-making.

Results: By opening up the data behind their research for exploration in KnowledgeHound, the team was able to discover new insights that weren’t included in the final reports. This deeper level of exploration led to the discovery of a completely new insight that impacted the future direction of a $1.4 billion product line.

Client Testimonial: “In a couple of hours, I discovered a new insight that I shared with our innovation team. They are now adjusting their product roadmap.”…..Read more

Also Read: New Product Release — Highlights For Rapid Reports