Data Science improves the business insights your company derives from data. Topptalent's data science services help businesses improve their decision-making by employing vast data sets to get actionable insights that augment business value by improving customer experience, churn and supply chain operations.
Machine learning (ML) enables computers to “learn” through data without explicit programming. Data scientists can create deep learning algorithms using techniques borrowed from ML, helping your company explore ways to improve operations through real-time data.
Data science, advanced analytics, and machine learning techniques are key to creating predictive models. Developers can work with your team to improve forecasting, customer classification, and many other activities.
Natural Language Processing
NLP enables computers to effectively process large amounts of natural, human language. Whether through voice or text data, NLP specialists can help your company employ language data for processing and sentiment analysis.
Data visualization communicates information clearly and efficiently via graphs, plots, and infographics. Expert data visualization designers can help your team make better decisions with data.
Development in SAS, SPSS, R, Python, Julia, and other languages simplifies and enhances statistical analysis. Data scientists can help your company leverage the benefits of statistical programming.
Data pipelines are the critical infrastructure that unlocks timely analyses, from regular reporting to ad-hoc modeling. Data scientists can help you better gather, unify, and structure data from multiple sources to support your company’s analytics.
We supply professionals proficient in software development, management consulting, data analytics, UI/UX, digital marketing, channel partnerships, financial management, project and product management, from our largely Singapore-based talent pool. Each talent is selected for their subject matter expertise and their experience working in managed teams. All talents come with a risk-free trial period so that you can ascertain their capability prior to starting officially.
What data science can do for your business
1. Gain Customer Insights
Data about your customers can reveal details about their habits, demographic characteristics, preferences, aspirations, and more. With so many potential sources of customer data, a foundational understanding of data science can help make sense of it.
For instance, you may gather data about a customer each time they visit your website or brick-and-mortar store, add an item to their cart, complete a purchase, open an email, or engage with a social media post. After ensuring the data from each source is accurate, you need to combine it in a process called data wrangling. This might involve matching a customer’s email address to their credit card information, social media handles, and purchase identifications. By aggregating the data, you can draw conclusions and identify trends in their behaviors.
Understanding who your customers are and what motivates them can help ensure your product meets their job to be done and your marketing and sales efforts are working. Having an understanding of reliable customer data can also inform retargeting efforts, personalized experiences for specific users, and improvements to your website and product’s user experience.
2. Increase Security
You can also use data science to increase the security of your business and protect sensitive information. For example, banks use complex machine-learning algorithms to detect fraud based on deviations from a user’s typical financial activities. These algorithms can catch fraud faster and with greater accuracy than humans, simply because of the sheer volume of data generated every day.
Even if you don’t work at a bank, algorithms can be used to protect sensitive information through the process of encryption. Learning about data privacy can ensure your company doesn’t misuse or share customers’ sensitive information, including credit card details, medical information, Social Security numbers, and contact information.
It’s the combination of algorithms and human judgment that can move businesses closer to a higher level of security and ethical use of data.
3. Inform Internal Finances
Your organization’s financial team can utilize the data science to create reports, generate forecasts, and analyze financial trends. Data on a company’s cash flows, assets, and debts are constantly gathered, which financial analysts can use to manually or algorithmically detect trends in financial growth or decline.
For example, if you’re a financial analyst tasked with forecasting revenue, you can use predictive analysis to do so. This would require calculating the predicted average selling price per unit for future periods and multiplying it by the number of units expected to be sold during those periods. You can estimate both the average selling price and the number of expected units sold by finding trends in the historic company and industry data, which must be qualified, cleaned, and structured. This is data science at work.
Additionally, risk management analysis can be used to calculate whether certain business decisions are worth the potential downsides. Each of these financial analyses can offer valuable insights and drive business decisions.
4. Streamline Manufacturing
Another way you can use data science in business is to identify inefficiencies in manufacturing processes. Manufacturing machines gather data from production processes at high volumes. In cases where the volume of data collected is too high for a human to manually analyze it, an algorithm can be written to clean, sort, and interpret it quickly and accurately to gather insights.
For e.g, a company can create a machine-learning tool, which collects manufacturing data, identifies times of highest efficiency, and provides recommendations for replicating that high-efficiency state. As the algorithm gathers more data, it provides better recommendations for improvement.
5. Predict Future Market Trends
Collecting and analyzing data on a larger scale can enable you to identify emerging trends in your market. Tracking purchase data, celebrities, and influencers, and search engine queries can reveal what products people are interested in.
For instance, clothing upcycling has been on the rise as an environmentally conscious way to refresh a wardrobe. According to research by Nielson, 81 percent of consumers feel strongly that companies should help improve the environment. Clothing retailer Patagonia, which has been usingrecycled plastic polyester since 1993, leaned into this emerging trend by launching Worn Wear, a site that’s specifically designed to help customers upcycle used Patagonia products.
By staying up-to-date on the behaviors of your target market, you can make business decisions that allow you to get ahead of the curve.
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How are Topptalent data analysts different from others?
At Topptalent, we screen our data analysts to ensure we only match you with talent of the highest caliber. You'll work with engineering experts to understand your goals, technical needs, and team dynamics. The end result: expertly vetted talent from our network, custom matched to fit your business needs.
Can I hire data analysts in less than 48 hours?
Depending on availability and how fast you can progress, you could start working with a data scientist within 48 hours of signing up.
Are there subsidies if I hire a data analyst for my company?
Generally there would be wage subsidies if you hire a data analyst, we will advise what the wage credits could be and how to get it.