The ongoing developments and technological shifts in the data analytics marketplace have made it crucial for businesses to analyze various factors before engaging with companies that offer advanced data analytics solutions. Despite the ongoing advancements, challenges continue to proliferate with the growing data sets making data analysis and data visualization an uphill task. Part of this challenge may be attributed to the impressive power of data analytics solutions and technological developments. However, the impact of data analytics solutions are so powerful that companies today focus on investing in analytics by collaborating with the top data analytics solution providers.
Investing in analytics tools without possessing the basic capabilities is like building a house without a solid foundation, though you possess the materials you cannot put them to good use. Our analytics experts have listed the top five criteria that will help you choose the right data analytics solutions provider.
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#1 Data Security
Data irrespective of its source must be stored securely on-premises or in the cloud to avoid cyber-attacks and data breaches. Time stamping and source-proofing data generated from the web and mobile sessions will help retain its authenticity and integrity. Businesses that offer data analytics solutions to devise data management systems with enhanced security layers can help you store and maintain data securely by avoiding tampering and data breaches.
#2 Universal Accessibility
Ease of use and accessibility is another key factor to be considering while engaging with companies that offer data analytics solutions. Ideally, data analytics solutions must allow fast and easy setup and grant access to all the departments of a company that use data to make crucial business decisions. A complex data management platform will make it challenging for members of other departments to access data sets and draw insights. Data analytics solution providers that offer data management platforms that are easy to use and interpret will empower companies to analyze data to reap maximum benefits.
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#3 PII Accessibility
PII stands for personally identifiable information that empowers companies to identify the users it relates to. With stringent data protection regulations coming into effect, businesses have to ensure they adhere to the rules listed under the General Data Protection Regulation act. While companies will still have access to the data extracted from each session, putting control of the data into the hands of the data analytics solutions provider will help them tackle challenges associated with data management.
#4 Data Compression
With the proliferation of data sets, businesses now have access to huge volumes of valuable information that must be stored and maintained on-premise to ensure it’s accessible as well as secure. In such a scenario, it’s crucial to select data analytics solutions that can help you cost-effectively maintain such data sets. This way you will be investing less in the technology needed to compress and store data. Data analytics solutions that leverage data compression techniques to compress data can help you shrink the original data footprint to as little as 5%, resulting in a huge reduction in TCO.
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#5 Insight Automation
The use of traditional BI tools to analyze the massive troves of datasets generated by today’s digital businesses requires a lot of time and expertise. Data analytics solutions that leverage advanced analytics and machine learning techniques to mine such data sets will be able to isolate issues in real-time to support your agile business processes. This signifies that data analytics solutions providers who adopt advanced analytics tools and cognitive technologies can detect anomalies in your current data management system in a way that adapts to changes efficiently and effectively.
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Today, there are innumerable companies that offer advanced data analytics solutions and making big claims about the difference they can make to your business. However, it’s crucial to note that no two data analytics solutions would possess the same expertise and skill when it comes to addressing challenges in real-time. Which is why companies must dig deeper and analyze their ability to add value to your business. A data analytics solution provider should be capable of helping you define the overall solution architecture as well as the process flow to address your business challenges. So, regardless of who you collaborate with, it’s essential to first define your needs and design a robust foundation early in the journey.
Players in the US retail industry are forced to cut costs to stay afloat during the recession period. Though a pain point, cost-cutting offers a good head start towards achieving the desired sales and profit margins. The recent advances in data analytics and technology have made data analysis much simpler, helping retailers to identify and capitalize on new opportunities in the US retail industry. With retailers across geographies offering a diverse range of offerings use similar promotional campaigns, retail data analytics has turned out to be a key differentiator in the US retail industry, helping players make important business decisions with ease. This has made it crucial for retailers to not only integrate and analyze data obtained from different sources but to also leverage retail data analytics to improve their overall decision-making ability.
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Top Data Analytics Applications That Can Help Players in the US Retail Industry
The insurance industry is witnessing a consistent annual growth but companies in this industry are struggling when it comes to insurance penetration among consumers. Globally, insurance fraud has become a major concern for insurance companies. To tackle these challenges insurance service providers are investing huge resources and manpower in insurance fraud detection.
Data analytics solutions can help insurance companies to reduce exposure to fraud, and credit losses by the timely identification of all insurance risks.
Companies in the insurance industry are under tremendous pressure to ensure adherence to claims decisions while striking the right balance under regulatory pressures, growth of digital channels and proliferating competition. This is the reason they are turning their attention towards big data and analytics solutions to identify misrepresentation, detect insurance fraud, and prevent identity theft.
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Role of Data Analytics in Insurance Fraud Detection
Insurance companies can leverage big data and analytics to analyze their strengths and weaknesses first, to, detect insurance fraud. This can help them to identify gaps in their existing fraud detection framework. As a result, they can improve their insurance fraud detection techniques and modify strategies.
Quantzig’s analytics solutions can help companies in better management of insurance claims, underwriting, actuarial, pricing and marketing functions and insurance fraud detection. Request a FREE proposal to gain in-depth insights into our portfolio of analytics solutions.
Data analytics helps in identifying new trends and patterns in the process of insurance claims as they emerge. This can help insurance companies to seamlessly update their models and rules in the monitoring system to prevent insurance fraud. With this fundamental approach to insurance fraud detection, insurance companies can continuously monitor the billing and patterns off-line as well to identify abnormal insurance claims.
By leveraging our analytics solutions insurance companies can better understand customers’ credit behavior to determine the level of risk in claims and relevant policies to suit and benefit customers. Request a FREE demo below to know more.
Big data and analytics play a crucial role when it comes to data integration. It can help insurance companies in building effective insurance fraud detection capabilities by combining data from disparate sources. Also, data analytics helps companies in the insurance industry to integrate internal data with third-party data. By leveraging big data analytics insurance companies can integrate data sources with derogatory attributes such as bankruptcies data, criminal records, and foreclosures into a model and can address the transient behavior. Furthermore, big data analytics can help in uncovering anomalies in insurance billing to identify insurance fraud.
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Sales data is one of the valuable assets any company has as it provides useful insights on the internal business functions. Companies use their sales data to make informed decisions like when to raise or lower prices of their products or services. These decisions should not be driven by “gut feeling” rather companies should perform detailed sales data analysis to identify trends and patterns in their sales data. This can, further, help in determining both opportunities and potential threats. Also, with the help of sales data analysis, businesses can track the performance of individual product or service in real-time. Such insights can help businesses to make timely decisions in case of decrease or increase in sales of any particular product or service. Sales data analysis can also help companies to determine if they are meeting their sales goals by providing them with an easy, measurable way to track their performance. In this article, our sales analytics experts have highlighted a few important ways in which sales data analysis can help businesses to improve revenue growth and profitability.
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How to use sales data to boost revenue growth?
Centralized database to view data
To utilize sales data optimally, businesses need to have a unified view of sales data that includes all orders and inventory by product and category. If there is a lack of centralized location of such data, businesses might fail at defining the impact of one of their sales channels or product lines on their entire business. Also, a unified location of data allows companies to perform proper sales data analysis that can further facilitate accurate and timely decisions like when to move inventory from one location to another or markdown products.
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Utilize real-time sales updates
To uncover potential opportunities and threats, businesses need to track their sales every day even down to the minute. This is the reason why sales data needs to be updated in real-time. Sales data analysis in real-time can help businesses to analyze how price changes can impact the customer’s decision. Data visualization tools like sales dashboards can help in analyzing information quickly and respond to changing sales trends in real-time.
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Drill down sales data by location, product type or channel
To derive the desired result out of sales data, businesses must gauge their sales data by specific locations, product lines, or sales channels. Such granular insights can help businesses to understand what’s contributing the most to their revenue growth or causing the loss of revenue. Also, this helps to understand more precisely every aspect of sales and analyze sales trends over a period. Furthermore, this can aid in managing inventory, marketing, and finance functions efficiently.
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What is Manufacturing Analytics?
Manufacturing analytics is a technique that integrates big data, predictive analytics and industrial internet of things with the manufacturing processes to bring efficiency in the business operations. Manufacturing processes are successful when businesses can streamline their operations. This is where manufacturing analytics can help. Today manufacturers can leverage manufacturing data analytics techniques to examine, test and re-test every single process and implement innovative ideas to make improvements in the business operations. Manufacturing analytics can make manufacturing processes faster and more efficient by offering more focused and actionable insights that can help companies to fine-tune their production line.
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Benefits of Manufacturing Analytics
Manufacturers can maximize the operating time of critical assets by leveraging manufacturing analytics solution to anticipate their failure. By utilizing data analytics in manufacturing, businesses can gather historical data (structured and unstructured both) to gain in-depth insights into operations that can’t be assessed with conventional techniques. Using manufacturing data analytics, companies can identify the circumstances that tend to cause breakdown of a machine and monitor input parameters so they can intervene before breakage decreasing downtime. Furthermore, manufacturing analytics can help companies understand how downtime for a single machine can affect the manufacturing chain and how different configurations may improve overall efficiency.
Our analytics experts can help you make better decisions by visualizing how each aspect in your manufacturing chain impacts the final result. Get in touch with them right away.
Gain better insights into machine utilization and effectiveness
One of the major challenges that manufacturers face is wastage of time. While manufacturing chains can be built with efficiency in mind, different factors may play a contributing role in reducing the overall efficiency of the line because of poor installation, misuse, or simply a lack of downtime coordination. By combining existing IoT systems with manufacturing analytics solutions, companies can gain real-time insights into how well their manufacturing lines are operating. Also, it can help in generating actionable insights to help companies realize real improvements in the overall process.
Improve demand forecasts
Any product manufactured today aims to cater the demands that will emerge in the near future. This is the reason why demand forecasts are important from a business perspective. Demand forecasts guide a production chain and help identify the reason between strong sales and an unused inventory. For most companies, forecasts are based on historic values and not on more actionable forward-looking data. By leveraging manufacturing analytics solution, manufacturers can combine existing data with predictive analytics to build a more precise projection of future purchasing trends.. These insights are derived not just from previous sales data but from how well current manufacturing processes are operating, leading to smarter risk management and less production waste.
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Better warehouse management
Storage is generally the most overlooked aspect of the manufacturing process. Every stage is important when products are ready to be shipped especially in a world that is increasingly embracing zero-inventory models to reduce overstock scenarios. This is where warehouse management is important. Establishing an efficient warehouse management system can further improve product flow management, and improve business operations, as well as the bottom line. Manufacturing analytics framework makes it easier to understand how to improve your inventory and manage your warehouses better. This can, further, help in improving manufacturing KPIs and processes. By incorporating a robust manufacturing analytics solution companies can build a more granular understanding of how their production line operates, and how they can streamline it to avoid unnecessary costs
Manufacturing leaders today are visionaries, pioneering increasingly efficient methods to produce and move physical goods while thinking beyond cost savings, productivity, and risk reduction. Future survival needs manufacturers to become nimble and analytics driven. This can help organizations minimize risk and seize opportunities through actionable operational insights and confident decision making. Manufacturing analytics solutions from Quantzig can help companies to fine-tune their production operations for minimal cost and risk while capitalizing on data as an asset that can further help them deliver innovative services and quality products. We, at Quantzig, deliver proven value and help leading companies unlock the immense potential of their digital transformation through our customized manufacturing analytics solutions.
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The oil and gas industry has played an important role in the economic transformation of the world since the industrial revolution. Advanced technologies and data analytics techniques can help the oil and gas industry to tackle a series of challenges such as frequent budget and schedule overruns, difficulties in attracting talent and demands of climate change accountability. Digitalization can act as a key to tackle these challenges and provide value to all the stakeholders of companies.
“With digital transformations paving the way into the oil and gas industry, companies can harness a plethora of data to reduce operational expenses, down well times, and lessen risk.”
However, the oil and gas industry has fallen behind in terms of digitalization and is unable to utilize the real-time data and insight gathered by connected technologies. Oil and gas companies can gather data from a variety of sources, such as sensors embedded in wells or machine-to-machine data. With multiple sources of data, digitally mature companies can gain the potential to glean key insights and analytics to stay ahead of the curve. By realizing the potential of digital technology oil and gas companies can achieve desired results such as increased revenues, improved safety, reduced costs and reliability of business operations.
Today companies in the oil and gas industry need to use data analytics solutions to analyze interconnected market forces and optimize processes. Our analytics solutions can help. Request a FREE proposal to gain better insights into our portfolio of services.
How digital transformation is revamping the oil and gas industry?
Indicator #1: Digitization is enabling companies to gain a competitive advantage
Today companies in the oil and gas industry are looking to integrate solutions and technologies that will give them a competitive edge, provide critical insight into core business practices and operations, and above all, reduce costs. Fortunately, with digitization, innovative technology is becoming easily affordable and companies in the oil and gas industry can leverage digital technologies such as real-time data streams, mobile technology, and embedded sensors. This can, further, keep them constantly stay updated on day-to-day business operations
Indicator #2: Digitalization contributing to lower production costs
One of the major challenges that companies in the oil and gas industry are facing is rising production costs. This is the reason why companies in the oil and gas industry are increasingly relying on big data and analytics solutions to optimize business functions. By adopting digital technologies, companies in the oil and gas industry can easily manage, measure, and track all the data coming from different sources. Furthermore, this can help them to gain actionable insight and maximize their quality and output and minimize the waste throughout the process. As a result, companies can become more productive and efficient in the long run.
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Indicator #3: Improving agility with real-time data
Companies in the oil and gas industry are now realizing the increasing role that digital transformation play in becoming agile, faster, and better equipped to adapt to challenges and market conditions. Despite the current economic downturn, oil and gas companies are funneling a huge amount of money into funding innovative technology that can help them optimize production and minimize costs. Also, with the effective use of digital technologies, companies in the oil and gas industry can become more productive, efficient and agile. The real-time data and insight can help companies in the oil and gas industry to determine the root cause of malfunctions, machinery failures and defects in near real-time and make precise and smart business decisions.
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Indicator #4: Cross-industry collaboration creating new opportunities
With the economic downturn, companies in the oil and gas industry are forced to look for cheaper and more efficient ways of producing oil and gas. This has developed the need to build partnerships and collaboration across industries. Consequently, big players in the oil and gas industry are shifting towards favoring smaller companies which are specialists in specific areas of the oil and gas environment. Such partnerships can help companies to focus on their core competencies while outsourcing cloud-based solutions and cyber-security systems.
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The Business Challenge
Data obtained from every source can help you unearth actionable insights if analyzed accurately, and transportation data is no exception. Having said that, it’s crucial to note that transportation data analytics has the potential to improve logistics management, as well as enables businesses to optimize transit routes and services. Leveraging transportation data analytics to develop route maps can help businesses to optimize the logistic workflow, which in turn, will result in a drastic reduction in congestion levels and time spent in transit.
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The manufacturer’s delivery team was complex and comprised of hundreds of employees and partners. The use of outmoded logistics tracking systems made it difficult to track, update, monitor, and deliver products in a timely manner. Also, the outdated legacy systems were difficult to maintain and proved to be of no use in logistics management. Such factors along with the ongoing loss made it crucial for the client to replace the legacy system with a more efficient logistics work flow.
Solution Offered and Value Delivered
The CPG manufacturer approached Quantzig to leverage its expertise in transportation data analytics and drive significant improvements in the logistics work flow. Our transportation data analytics solutions helped the client to gain in-depth insights into their logistics routes through advanced backend dashboard that provided real-time insights based on transportation data.
Through our transportation data analytics solutions we helped the client to revamp their current logistics workflow and achieve the desired level of efficiency. In addition, it’s essential to note that transportation analytics improved their logistics and route planning capability and helped them achieve huge savings on maintenance and renewal.
Ensure the efficient transportation of people and goods using advanced strategies built from the insights of transportation data analytics.