In 2004, Walmart had a big challenge in front of it–how to quickly predict what their customers would buy in the days leading up to a hurricane. And what did they do to get the data? Instead of going the traditional way, that is, of analyzing sales data and then determining customer behavior, the retail giant went the big data way.
Walmart analyzed massive datasets of previous buying patterns, and its analysts spotted an unlikely trend — sales of Pop-Tarts and beer soared ahead of hurricanes. Armed with this knowledge, they made sure these items were clearly displayed in their stores in the run-up to the storm. And what did this do? It led to a substantial rise in sales and customer satisfaction!
This anecdotal evidence illustrates the impact that big data has on predictive accuracy, a tool that is being widely utilized by financial analysts of major firms across the world.
Want to know how Netflix transformed content creation and recommendations by using big data to analyze viewing habits?
It analyzed trends, such as what people were watching, skipping, and rewatching, and based on those patterns the streaming giant produced hits like “House of Cards” — designed exclusively with its users in mind.
This shows how predictive analytics can turn raw data into actionable insights — something financial analysts can apply when predicting market trends and customer behavior.
Big data is one of the most transformative tools out there at your disposal.
Not sure if you can handle the change? Why not hire a financial analyst and find out how these professionals use big data to improve forecasting accuracy and drive business success.
But What Exactly is Big Data?
Large, complex datasets that traditional data-processing tools find beyond their scope to handle are what is referred to as big data. Big data encompasses structured, semi-structured, or unstructured datasets, typically derived from the following:
Market Data: Stock prices, trading volumes, and economic indicators.
Consumer Behavior: Purchase patterns, online behaviors, social media sentiment.
IoT Devices: Real-time sensor readings from connected devices.
News and Events: International news events, geopolitical dynamics, and regulatory changes.
Now that you know what big data is and how businesses are using it to stay ahead in the game, let’s find out how it can help you grow your business.
5 Reasons Why Financial Analysts Are Turning to Big Data for Accurate Forecasting
1. Enhanced Data Collection
Big corporations use big data tools to extract information from a variety of sources, including proprietary financial systems, social media, and third-party data providers. These tools guarantee that data is all up to date and also fits in with the forecasting objectives. This is especially crucial in fast-moving markets. Why? Because analyzing stale data can lead to erroneous forecasts.
Another advantage of using big data analytics is that companies can process and analyze enormous quantities of data in real-time. This helps enhance their decision-making process.
To do this adequately, these companies use machine-learning algorithms. These algorithms detect patterns and trends that would not otherwise be visible if conventional analysis techniques were put to use. By using these evolved data aggregation practices, financial analysts can boost the precision of their predictions, enabling successful sourcing and budgeting.
2. Machine Learning and Advanced Analytics
Several insights may get overlooked when businesses use traditional methods for forecasting. And advanced analytics and machine learning are what come to their rescue. Financial analysts can use them to improve their forecasting accuracy in the areas of predictive and sentiment analytics.
For example: Amazon employs machine learning powered by big data to anticipate customer demand. By studying purchase history, browsing habits, and seasonal trends, Amazon optimizes its inventory and pricing strategies which allow for a worry-free customer experience. Financial analysts could take a cue from this method to predict and adapt to potential shifts in the markets.
3. Real-Time Forecasting
Big data allows financial analysts to regularly update their projections in real-time, keeping businesses nimble and responsive to shifts in the marketplace. Here is something data analysts can do at their end that can benefit businesses:
- Real-time data integration: If new data continuously gets integrated into the model, analysts can continuously adjust the model to suit the changes in the market. This enables more accurate and timely predictions.
- Agility in Decision-Making: Sudden transformations in the market demand businesses to react promptly to changing dynamics. At such a time real-time forecasting enables quick strategy adjustments, which helps minimize potential losses and opens doors to new opportunities.
4. Risk Management
Big data is essential for monitoring and controlling risks by detecting abnormalities and predicting possible disruptions such as the following:
- Anomaly Detection: Big data tools can analyze transaction data and other financial records to identify irregularities that may signal fraud or other risks.
- Predictive Risk Analysis: Technology can provide big data on economic disruptions and predict their intensities — such as market crashes or geopolitical events — it helps businesses to be prepared and mitigate risks.
5. Customizable Dashboards
Financial analysts create dashboards, which stakeholders use to visualize big data insights. This makes it easier for stakeholders to interpret the financial forecasts and act on them. Here’s how.
Customized dashboards help analysts visualize complex datasets in an easy manner. Such dashboards use charts, graphs, and other visual aids to help analysts draw meaningful insights. Most contemporary dashboards have an interactive component that enables users to delve into specific data points.
With the help of these methods, financial analysts can harness the full potential of big data and deliver more accurate forecasts, effective risk management clues, and actionable insights to organizations.
Big Data Forecasting: Why You Should Hire Financial Analysts
Still in two minds whether to hire a financial analyst? These financial wizards possess unique skills and expertise, particularly when it comes to harnessing big data. Here’s why you should add an experienced financial analyst to your team:
- Technical Mastery: They are adept with big data tools such as Python, R, SQL, and business analytics platforms.
- Strategic Insight: They do not just crunch numbers; they give you actionable insights that align with your business goals.
- Flexibility: They rapidly adapt to new data sources and emerging technologies to ensure forecasts remain relevant and accurate.
- Cost-effectiveness: Their enhanced forecasting accuracy assists businesses in the efficient allocation of resources and reduced financial risks.
Shaping the Future: Big Data in Action
The combination of big data with financial predictions is only the tip of the forecasting ‘iceberg’. As technologies such as artificial intelligence, blockchain, and quantum computing change and evolve in the coming times, financial analysts will be able to predict better using these powerful tools.
Tesla is a good example of the kind of potential that big data has. By relying on big data, Tesla was able to ensure their supply chain and innovation cycles were fully aligned with market demands.
Tesla uses big data collected from its vehicle fleet to improve its forecasting and optimize production. Through real-time analyses of vehicle performance and customer feedback, Tesla guarantees its supply chain and innovation cycles match market demand.
In the coming times, more companies will adopt similar strategies and the role of financial analysts in leveraging big data will become even more critical. To stay ahead in the game, you, too, will need to hire financial analysts who understand big data. These financial experts will take your business to the next level by transforming raw information derived using big data into actionable insights. Ready to make big data your biggest asset?
