Overwhelmed by the huge chunks of data that your business has to analyze every day? Want to learn how to use big data to create great value for your business?
If yes, then you’re in the right place!
In this article, we’ll explain how smart data strategies equal big profits for you and your business. And keep reading to find out how your business can skyrocket to success.
So get ready to learn how to harness the power of big data for business success in this data age!
Unveiling the Power of Big Data in Modern Business
Big data isn’t a new trend. It’s been around for quite some time. We get big data from different places, like social media, advertising campaigns, financial transactions and more.
With it you can:
- improve customer experience
- boost operational efficiency
- create new products and services
- gain a competitive edge
There’s an ever-growing volume of data that needs to be generated and processed. According to some reports, global data volume is expected to reach 175 zettabytes by 2025. That’s equal to a billion terabytes!
And with those bigger bytes to handle, there’s an increasing demand for big data solutions and services. Businesses need all the help they can get to be able to solve problems, optimize performance and create value.
Using big data services, a business can understand customer behavior and preferences. They’re better equipped to predict upcoming market trends and demand patterns. Using big data solutions also means a business can identify risks and optimize processes. They get enhanced quality and productivity and improve their customer satisfaction much more effectively.
Navigating the Data Deluge: Challenges and Opportunities
The Challenges
With the countless benefits that come with using big data solutions, there are some challenges that need to be overcome. Take a look at them below:
- Data quality
If the quality of data is poor, that can lead to mistakes, wasted time and resources, and even legal or reputational damages. So it’s important for businesses to have a high-quality big data solution in place.
- Data security and privacy
If there’s a security breach, then you can expect financial losses, legal liabilities, customer dissatisfaction or even damage to brand reputation. You’ll need great security measures to protect your data from internal or external threats.
Data privacy and ethics are also becoming more important because of the actual data involved. Big data means businesses collect and analyze large amounts of sensitive data like:
- health records
- biometric information
- location history
- online behavior
So make sure your business complies with relevant laws of data privacy and ethics like the General Data Protection Regulation (GDPR).
- Data integration
Data integration is important for decision-making. But it can be difficult because of the complexity or inconsistency of data sources and formats.
So businesses need to have appropriate tools and methods for better data integration. For example, OpenX has three different ways for you to integrate your data with the platform:
- By using Open Audience
- Adobe Audience Manager
- OpenX’s Platform API
Like other high-quality big data solutions, OpenX also lets you use your own data or third-party data sources to level up your advertising campaigns.
- Data visualization:
Data should always be more accessible or persuasive for different audiences like stakeholders, customers, employees or the public. But balancing the aesthetics, functionality and accuracy of data presentation can be a little hard.
That’s why businesses need to have clear-cut strategies to create compelling data visualizations like charts, graphs, maps and infographics.
The Opportunities
Using big data has a few great opportunities. With smart data strategies, it can provide huge benefits for businesses like:
- Data-driven innovation
Data-driven innovation can help businesses stand out from the crowd and generate new sources of revenue. Some great examples include Netflix and Spotify. Netflix uses big data to personalize its content recommendations for its users. Spotify uses big data to create customized playlists for its listeners.
- Data-driven optimization
Data-driven optimization equals increased efficiency and quality. Businesses can also reduce costs and risks while maximizing their profits. For example, Amazon uses big data to optimize its inventory management and delivery systems.
- Data-driven decision-making
With data-driven decision-making, businesses can improve their accuracy and reliability.
OpenX is a company that has data-driven decision-making as one of its core values. It uses big data solutions to optimize performance and create innovative solutions for its clients. Other companies like Google use big data to rank search results while Facebook targets its ads with decisions made with big data in mind.
From Raw Data to Smart Insights: The Data Transformation Journey
To fully reap the benefits of big data, your business needs to embark on a data transformation journey. This has four main stages:
- Data collection:
It’s the first and most fundamental stage because it judges the availability and quantity of data that can be used for analysis, while still collecting the data.
That’s why businesses need effective strategies for collecting reliable data that meets business objectives.
- Data storage:
This stage determines the accessibility, security and durability of data. That’s why it’s important to have appropriate platforms and solutions for storing large, complex and dynamic data.
- Processing data:
This is the third and most challenging stage of the data transformation journey. At this stage, you can judge the usability, consistency and quality of data that can be used for analysis. So it’s important to have efficient tools for processing large, complex and dynamic data. This will ensure their data validity and reliability.
- Data analysis:
This stage is where the value and impact of data can be used for decision-making. Using the right tools ensures that businesses know how to use their data insights for innovation.
OpenX prides itself on using the data transformation journey as part of its successful business strategy. The company partnered with Sigmoid to standardize and migrate its data platforms to Google’s centralized BigQuery data lake. This resulted in better customer experience and lesser expenses.
OpenX and Sigmund also partnered up to drive operational efficiency and data-driven decision making together, using real-time data access and interactive technology.
These examples show that if you let your business embark on a data transformation journey, it can only bring success and help level up your business model from data-ignorant to data-informed.
Leveraging Data for Competitive Advantage: Strategies for Success
To stand out from the crowd, a business needs a great strategy. Some of the key elements of these are:
- Data vision:
A business that uses big data services can create its own data vision. This represents the desired outcome that a business wants to achieve by using big data. Whether it’s becoming a data-driven leader or innovator in its industry.
It also reflects the core values of a business. For example, one of OpenX’s core values is innovation through using data-driven decision-making and actions.
- Data culture:
Your business’s data culture shapes how you collect, store, process, analyze, and use data in your business’s daily operations or decision-making.
Having a positive, supportive, and collaborative data culture can create a data-driven environment within your organization. And as a bonus, it encourages data stakeholders and users to use big data effectively and efficiently.
- Data governance:
Good data governance covers the aspects of quality of data, security, ethics, and reporting that need to be enforced by a business when using big data.
It also involves the roles and responsibilities that need to be assigned to users when using big data. So make sure your business has a comprehensive and transparent data governance framework.
Revolutionizing Decision-Making Through Data-Driven Insights
Having a big data solution or service means that you get data-driven insights. These give huge benefits like:
- Enhancing accuracy
- Increasing reliability
- Enhancing agility
- Improving impact
Businesses can use these insights to respond to changing customer needs and market trends by using data to predict better decisions. It lets businesses achieve their strategic goals by using data to improve their key performance indicators (KPIs), return on investment (ROI), and value creation.
That’s why OpenX is always looking for new ways to increase the usage of its big data. The company has up-to-date big data services that help them automate reporting and double up on security of the data. This lets them focus on bringing more value to their clients with creative solutions and using big data to make more profitable decisions.
The Role of AI and Machine Learning in Extracting Value from Big Data
Where there’s big data, there’s AI and ML. These two can help create value in three ways:
- Data processing
- Analysis
- Visualization
AI and ML can help businesses process big data faster and easier by automating certain tasks. For example, AI and ML can help businesses use natural language processing (NLP) to process text data. AI and ML can help businesses analyze big data better by generating information and patterns from data that wouldn’t be obvious at first.
Successful businesses create realistic data images and interactive visualization for data exploration or manipulation. OpenX is one such company that believes in the power of AI and ML. It’s even a founding member of the OpenXLA Project.
Data Security and Ethics: Safeguarding Information in a Data-Driven Age
Some key aspects of data ethics are:
- Data consent
- Protection of data
- Data accountability
Make sure that you’ve obtained explicit data consent from users before using their data for any purpose. You’ll also need transparent data protection policies that can protect data from any potential risks. It’s also important to make sure that your business uses big data in a fair and ethical manner.
Real-World Applications: Industries Transformed by Smart Data Strategies
Some of the examples of industries that have been transformed by smart data strategies are:
- Healthcare
The healthcare sector uses smart data strategies to improve patient care, diagnosis, treatment and research. Healthcare providers use big data to monitor patient health conditions, predict patient outcomes and even prescribe personalized treatments.
- Education
Educators can improve student learning, outcomes, performance by using big data to personalize learning content and feedback. They can also track student progress and analyze learning patterns to optimize the curriculum design.
- Retail
The retail industry uses big data to improve customer experience. For example, retailers use smart data strategies to understand customer behavior and preferences. Then, they can predict customer demand trends and recommend products to them.
- Finance
Financial institutions use big data to analyze market trends and optimize portfolio pricing. They use smart data strategies to improve financial performance and risk management.
- Advertising
Advertising companies have used big data to create more personalized and relevant ads for consumers based on their behaviors, needs and preferences. They can segment their audiences and target them with the right messages at the right time and place.
OpenX has even been able to improve the efficiency and effectiveness of its clients’ advertising campaigns. By incorporating big data solutions, OpenX can deliver insights and analytics to their clients and create the right solutions for them.
Innovative Tools and Technologies: Empowering Businesses in the Data Age
Some innovative tools and technologies that can empower businesses in the data age are:
- Cloud computing
Cloud computing gives you cost-effective solutions for collecting, analyzing, and visualizing big data. For example, businesses can use cloud computing platforms like Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) to host their big data applications and solutions.
In 2019, OpenX moved its entire infrastructure to the Google Cloud Platform. It’s the first major exchange to ever move completely onto the cloud. And for good reason, too. This saved time and resources and improved company performance. The move also meant that OpenX would have access to the latest technologies and services.
- Artificial intelligence (AI) and machine learning (ML)
Businesses can use AI and ML technologies like TensorFlow, PyTorch or OpenAI to build their big data applications and solutions.
- Data visualization
Data visualization provides compelling solutions for presenting, exploring, or manipulating big data. Businesses can use a smart data strategy that involves data visualization tools like Tableau, Power BI, or D3.js to create charts, graphs or infographics for their big data.
The Future of Big Data: Trends and Predictions for Business Evolution
Big data has a bright and promising future that can shape the evolution of businesses and industries in the data age. Let’s take a look at some of the trends below:
- Data democratization
Data democratization can help businesses by empowering their data stakeholders and users to access big data without any barriers. For example, businesses can use data democratization platforms like OpenX to let their users look at big data insights.
- Data fusion
Data fusion is a game charger for businesses. They can integrate big data from different places and use data fusion platforms or solutions like Google Cloud Data Fusion to collect big data from different places like clouds, databases, APIs, etc.
- Data literacy
Data literacy means businesses can train their data stakeholders and users to use big data more effectively. For example, there are data literacy platforms like Qlik Sense where businesses can learn how to use big data for different purposes.
Measuring Success: Key Performance Indicators for Data-Driven Initiatives
Businesses need to measure the performance of their data-driven initiatives. And that’s where Key Performance Indicators (KPIs) come in. KPIs can even provide recommendations for their data activities.
Three KPIs to keep in mind are:
- Quality of data
- Data security
- Value of data
A business can measure its data quality by using metrics like error rate and consistency rate.
Data security is another KPI that measures how safe and secure the data that a business uses for its data-driven initiatives is. So, for that, a business can use metrics like breach rate and recovery rate.
Lastly, a business can measure its data value by using metrics like ROI and customer satisfaction.
Overcoming Challenges: Navigating Obstacles on the Path to Data Transformation
Some of the common challenges obstacles or barriers that businesses may face are:
- Data silos
Data silos can prevent businesses from accessing big data. For example, businesses may face data silos due to technical or legal factors that create boundaries between different units within an organization.
- Data skills gap
A gap in data skills can limit businesses’ capacity by restricting them from using big data effectively. A business can face a data skills gap due to the lack of talent or resources.
- Data resistance
Data resistance can reduce trust in big data and its insights or solutions. For example, businesses may face data resistance because of their users’ uncertainty about validity and reliability of big data and its insights or solutions.
Final Thoughts
Big data is a powerful trend that can boost businesses in the digital age today.
They can harness the power of big data to create value for themselves and others. But this means your business needs to overcome any challenges along the way. That’s why it’s important to adopt a strategic approach to use big data for business success.
