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Big Data

Big Data Challenges in the Media and Entertainment Industry

The media and entertainment industry is growing at an unprecedented rate, with companies finding it difficult to keep up with the pace. The challenges arise due to pressures to keep the costs down while trying to improve revenues. Further complications arise as the media consumption habits of customers are highly fragmented. The trend of one big company dominating the market is gradually fading away, providing an opportunity for small players to complete successfully. One of the most significant trend observed in the media industry is the shift in media platforms from traditional channels to online mediums. As a result, it paves the way for the media industry to implement big data and data analytics technology to gain more profound audience insights. With a new source of data available to the media companies each day, companies can efficiently understand customer needs and deliver content that pleases the audience. However, with the rapid adoption of digital technologies, the media industry does face a few big data challenges which slows down their progression. To fully realize the potential of digital Free demotechnologies, the companies should successfully tackle these big data challenges.

Big data challenges in the media industry

Data privacy concernsData Privacy

Numerous leaks of personal information and media have been making the headlines recently. Consequently, consumers are being more sensitive towards their data and are concerned on how their personal data is being used. Additionally, policymakers have also addressed their issues and have implemented regulations for businesses that handle personal data. Such big data challenges can pose problems when it comes to accumulating sufficient user data, without which accurate analysis cannot be performed. Regulations have also been in place for companies that broker personal data to media houses.

Lack of financial muscle

One of the most significant big data challenges in the media industry is the lack of financial muscle for media start-ups and SMEs. While accounting for cost factors to implement data analytics, companies need to look at various factors including data storage costs, infrastructure costs, data processing costs, and human resource costs. Although it is relatively easy to start a new company producing content, games, or apps, it can be tough to scale up without significant investments. Thankfully, the advent of cloud storage and SaaS solutions have provided a way out for start-ups and SMEs.

Difficulty in talent acquisition

Talent Acquisition

There is a significant imbalance in the supply and demand of data scientists all across the world. The imbalance is mostly in terms of shortage of supply of analytics professionals. Furthermore, the demand for data scientists has been increasing exponentially, and there aren’t many professionals to fill the void. As a result, companies have to pay out hefty salaries to such professionals usually upwards of $100,000. The problem of talent acquisition is one of the key big data challenges in the media industry, which cries out for professionals in data journalism and product management.

Low penetration rates of high-speed broadband

A large part of the content delivered to the audience today is via online mediums. To facilitate this, high-speed broadband is a must. However, the penetration rates of high-speed broadband services haven’t been that impressive across the world as it is limited mostly to metro cities. Firstly, it reduces the potential customer base and then gathers data from only urban segment consumers. Analysts cannot gain insights into customers who lack access to high-speed broadband and thus resort to traditional mediums.

Piracy, copyrights, and account sharingAccount sharing

Piracy and copyright issues have been there in the media and entertainment industry for a long time. However, the advent of digital medium has created new big data challenges, the problem of account sharing. For the majority of video streaming sites, a large number of people gain access by sharing account information and passwords. Analysts will have a tough time performing analysis on customer preferences as they cannot pinpoint the demographic details of the user. Both the child and the adult may be using the same account, so an effective judgment is impossible on whether the child or the adult prefers a specific genre.

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big data analytics

Big Data Analytics Helped a Client to Ease Data Processing & Improve Service Efficiency by 12%

“Considering the unique needs of our business and the complexities of our data sets, Quantzig’s big data analytics experts did an outstanding job in laying an analytics roadmap.”

About the Client

The client is a leading mobile marketing automation solutions provider based out of Austria that measures mobile app engagement and provides granular, analytical insights to its customers. They also empower companies to send customized marketing messages to meet the unique needs of the end-users across multiple channels such as in-app, push, email, web, and other media.

The Business Challenge

In today’s economically uncertain era, many leading businesses have come to appreciate that the key to better decisions, more effective customer engagement, sharper competitive edge, hyper-efficient operations, and compelling product development is- Data. The challenges faced by business is not due to the shortage of raw materials, but due to the lack of domain expertise and analytical skills to turn the unstructured, huge volumes of “Big Data” into actionable insights.

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The marketing automation segment witnessed accelerating growth only after 2014, around the same time when mobile users first outnumbered desktop users. Today, unstructured online data sets have grown exponentially making it crucial for businesses to leverage analytical methodologies to analyze these data sets. Moreover, the ongoing data deluge signifies that marketers pursuing consumers need to deploy a way to closely understand the end-users of their applications. This is crucial because once they analyze consumers’ mobile behavior, they can hone their core mobile marketing competencies to match their requirements.

The client- a mobile marketing automation company (MMAC), needed a massively scalable big data analytics platform to inform its marketing-oriented customers about how well their mobile applications were engaging mass-market consumers. The company sought a ‘single version of truth’ platform that was also affordable and user-friendly for the application developers, typically marketers who weren’t necessarily data scientists.

The client’s challenges spanned three core areas including:

  • Velocity
  • Variety
  • Volume

Still unsure about how big data analytics solutions can help you drive profitable growth? Talk to our analytics experts for comprehenisve insights.

Solution Offered and Value Delivered

As frontrunners among big data analytics solution providers, we exhibit proven big data analytics capabilities in successfully handling the entire lifecycle of big data implementation including deployment, development, maintenance, and support. Having worked on advanced technologies and big data analytics tools that are leading the big data ecosystem, our analytics experts poses the capability to develop big data analytics frameworks that address all the functional components including data provisioning, data management and data consumption. 

We adopted a comprehensive three-step approach to big data analytics that offered a 360-degree view of consumers interactions with mobile apps. The insights also enabled the client to choose what changes might boost usage, increase business, and retain consumers – and improve the ROI of their marketing investments. Also, by deploying visually interactive big data analytics dashboards we offered in-depth insights tailored specifically to each app developer and its offerings.

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Phase 1

The first phase of this big data analytics case study revolved around data cleansing, data aggregation, and data analysis. A detailed analysis of customer data obtained from millions of smartphones helped the client to gain comprehensive insights into the demands of the end-users.

Phase 2

The second phase of the big data analytics engagement focused on analyzing and translating user behavior across a broad range of mobile apps. It also involved analyzing data on time-series information, sequential action, geo-location, and others across all types of applications and mobile devices.

Phase 3

The final phase of this big data analytics engagement revolved around data visualization and dashboarding to help the client analyze user paths while making in-app purchases.

BIG DATA ANALYTICS

Business Outcome

With the help of our big data analytics solutions, the mobile marketing automation solutions provider was able to improve their service efficiency by 12% and expand their capabilities, beyond supplying its customers with aggregated data about users of their applications. Data visualization and the devised big data analytics framework enabled the client to track and gauge customer engagement rates. Our big data analytics solutions also offered insights on how they could improve the UI of their applications to improve customer engagement.

Would you like to learn more about our big data analytics capabilities? 

clickstream data

Clickstream Data Analysis: Cost-Effective Approach for Businesses to Succeed in 2020 and Beyond

What is Clickstream Data?

Clickstream data refers to the data generated by the users when they perform any activity or when they navigate over a web application. It comprises valuable information for businesses that can help them quantify user’s behavior and get an idea of how effective their website is at driving sales. Also, with the help of clickstream data, businesses can understand the user experience, based on their navigation patterns. Furthermore, by analyzing clickstream data businesses can predict which page customers are likely to visit next, improve their marketing strategy and come up with better recommendations.

Talk to our analytics experts to know how our big data analytics solutions can help you visualize online visitor interactions through online channels.

CLICKSTREAM DATA ANALYTICSBenefits of Clickstream Data Analysis for Businesses 

Click path optimization

Clickstream data analysis can guide businesses in website traffic analysis that can further help them in tracking the path the user takes while navigating through their website. As a result, businesses can gauge metrics that affect user experience such as the number of pages visited, page loading timings, the amount of data transmitted, and frequency of users.. Furthermore, by gaining such useful insights through clickstream data analytics, businesses can optimize the click path by making minor changes to the website to reduce bounce rates and increase conversions.

Our clickstream data analytics solutions enable businesses to track KPI’s and gain insights into customer buying behavior. Request a FREE proposal to gain in-depth insights into our analytics solutions.

Market basket analysis

Clickstream data analysis can pave the way for market basket analysis that can give them a better understanding of aggregate customer purchasing behavior. Also, by analyzing market basket, businesses can discover common interests of customers and common paths they take to arrive at the purchasing decision. Such valuable information can help businesses to determine the most productive path a site user can take for researching and buying a product.

Quantzig’s real-time data monitoring and clickstream data analytics solutions can help you observe user activity and determine the impact of your marketing campaigns. Request a FREE demo below to know more.

Next best product analysis

By leveraging clickstream data analytics, marketers can conduct the next best product analysis (NBP). With the help of this analysis, businesses can analyze what products customers prefer to buy together. This can further help them send real-time offers on such products to the customers to improve customer experience. Consequently, this can improve sales and revenue growth in the future.

Better customer segmentation

Clickstream data analysis offers in-depth insights into how individual customer segments behave. This can further help them to personalize customer experience at every touchpoint by analyzing customer behavior and interests in real-time. Additionally, customer segmentation at the granular level can establish another level of transparency and trust with customers and improve customer loyalty and retention.

To learn more about clickstream data analytics and its benefits, request for more information right away!

Big data analytics

Big Data Analytics Framework Empowered an Oil and Gas Company to Reduce Operational Costs by 37% Through Continuous Process Improvements

The client is a leading multinational oil and gas industry player, based out of Austria. The company boasts an impressive number of 6,000+ clients worldwide and employs over 10,000 employees. The oil and gas company wanted to devise a big data analytics framework that supports data acquisition, aggregation, transformation, and cleansing to create an enterprise data management platform that will serve as a single source of truth and help make crucial business decisions.

The Business Challenge

Modern big data analytics tools and cognitive technologies have been proven to be useful in maintaining and analyzing huge troves of data sets generated by businesses across industries. In the oil and gas industry, big data analytics helps improve data management, identify and map oil reservoirs, and optimize operational costs. With the generation of huge volumes of unstructured data sets from sensors, oil and gas companies have found themselves in a fix and are looking at capitalizing on new opportunities by leveraging advanced big data analytics solutions. Apart from offering actionable insights to improve decision making, big data analytics helps oil and gas companies to leverage big data to improve recovery rates, reduce environmental impacts, and avoid accidents.

Request a FREE proposal to find out how our big data analytics solutions can help your organization navigate its next. 

The current data management platform deployed by the client was expensive and offered limited scalability, due to which data was being underutilized and choked in their data storage systems curtailing its processing ability and giving rise to challenges such as high processing costs, limited analytical access to data, constrained EDW capacity, and inability to process unstructured datasets. To tackle these challenges, they wanted to leverage Quantzig’s big data analytics solutions and deploy a robust data management platform to effectively store and manage the growing complexities of the unstructured data sets. 

big data analytics

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Solutions Offered and Value Delivered

We adopted a comprehensive three-pronged approach to help the client tackle the challenges around data storage and data processing.

Phase 1

Partnering with the client’s data management team, we undertook a detailed industry assessment to understand their current big data analytics capabilities, scalability bottlenecks, and other factors hindering growth.

Phase 2

Our big data analytics team collaborated with the oil and gas client to devise an end-to-end big data analytics framework to tackle their challenges.

Phase 3

The third phase of this big data analytics engagement focused on deploying a big data platform to help them improve their analytical capabilities, understand the customer needs better, and generate more revenue opportunity.

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Our big data analytics solutions also empowered the client to:

  • Store, maintain, and process data as they moved through various stages of the data lifecycle
  • Achieve a 37% reduction in operational costs with continuous process improvements
  • Develop a big data analytics roadmap to scale business processes and analyze unstructured data sets
  • Demonstrate significant improvement over current ad-hoc analytics capability

Why Choose Quantzig as Your Big Data Analytics Solution Provider?

The staggering volumes of unstructured sensor data have given rise to several data management challenges in the oil and gas industry. To tackle these challenges, businesses must comprehend the pieces of information and extract actionable insights. Backed with powerful big data analytics tools and over a decade of experience in working with clients across industries, our big data analytics solutions can help you do just that by breaking down data silos to unearth valuable insights to act upon.

Request for more information to learn how we can help you tackle the complexities associated with ustructured data sets. 

sensor data analytics

Sensor Data Analytics: Helping Manufacturing Companies to Uncover New Opportunities

With the growing popularity of digital platforms, customers, suppliers and business partners need greater agility, speed, and scale from manufacturers. As a result, there is a need for fully integrated and collaborative manufacturing systems that can respond in real-time to meet the changing demands and conditions in the supply chain. This is where sensor data analytics can help. Sensor data analytics has enabled companies to drive greater possibilities for different kinds of distributed data sharing and analytics. It can help manufacturing companies to extract actionable insights from embedded sensors to drive organizational improvements and profitability. Also, disparate and deployed industrial assets and connected devices can provide manufacturing companies with a unique touchpoint to real-world operations and conditions.

Quantzig’s big data analytics experts can help you improve operations, ensure compliance, perform predictive maintenance and better manage the uptime. Get in touch with them right away.

sensor data analyticsBenefits of Sensor Data Analytics for Manufacturing Companies

Benefit #1: Optimize production and enhance efficiency

Manufacturing companies have a plethora of data sets which are mostly underutilized as intricate access makes valuable insights sluggish. Sensor data analytics can add a new dimension to such datasets with connected assets and sensors. This can, further, help manufacturers to quickly capture, cleanse and analyze machine data. Consequently, valuable insights can be derived that can help optimize production and enhance the efficiency of performance.

Our sensor data analytics solutions can help businesses to leverage cognitive technologies to analyze and visualize machine data in real-time. Request FREE proposal to gain in-depth insights into our portfolio of big data analytics solutions.

Benefit #2: Predict machine failure and quality improvement

Sensor data analytics can help manufacturers to make better use of machines. It can help in automating the analysis of data from sensors within equipment and the actual operation of these machines. Also, with the help of sensor data analytics, manufacturers can determine when machines may need to shut off to prevent an issue. Furthermore, sensor data analytics can aid in aggregating data faster by leveraging advanced data management techniques. Consequently, the overall quality of production can be improved, helping manufacturers to build a better plan of action.

Gain real-time insight into your asset deployment, utilization, and resource consumption rate with our sensor data analytics solutions. Request FREE demo below to know more.

Benefit #3: Facilitate preventive maintenance

In the manufacturing industry, preventive maintenance holds immense importance. Sensor data analytics helps in preventive maintenance by reducing the issues found in devices by triggering alerts based on the data generated by machines. Also, sensor data analytics has the potential to automatically signal the repair of a machine when needed. This further helps manufacturers to take preventive measures and improve the efficiency of machines in the course of conducting business. Therefore, sensor data analytics can empower manufacturing companies to ensure that modern manufacturing processes meet future business needs.

To learn more about how sensor data analytics can help you improve your manufacturing processes, request for more information now!

pharmaceutical industry

How is Big Data Analytics Contributing to the Changing Dynamics of the Pharmaceutical Industry?

The use of big data is no longer limited to transforming customer-facing functions such as sales and marketing alone. In the pharmaceutical industry, big data analytics is helping companies to deal with declining success rates and stagnant pipelines. Big data analytics is creating immense opportunities for companies in the pharmaceutical industry to deal with complex business environments amidst the explosion of data sets. The effective utilization of these datasets can help pharmaceutical companies in drug development. Also, big data analytics has enabled companies to improve clinical trials, manage risks efficiently, and improve patient safety.

Our analytics solutions help pharmaceutical companies in medical cost management and drug development. Request a FREE proposal now to gain better insights into our portfolio of analytics solutions.

How is big data analytics revolutionizing the pharmaceutical industry?

Improving sales and marketing

Until recently sales and marketing were grey areas in the pharmaceutical industry. But by leveraging big data analytics, pharmaceutical companies can easily focus on specific geographical areas to promote their medications. Consequently, pharmaceutical companies can create targeted marketing campaigns, thereby saving both on time and effort. Therefore, the role of big data analytics has become even more critical in devising marketing strategies and sales plans.

Quantzig offers analytics solutions specific to the pharmaceutical industry that provide evidence-based insights to help drive better decisions and results in all commercial operations. Request a FREE demo below to know more.

Enhancing the efficiency of clinical trials

Clinical trials are an integral part of the pharma industry. The patients undergoing these trials must meet some prerequisites. Big data analytics solutions help companies merge the databases from multiple sources, to filter out patients who do not meet the basic requirements. Also, these solutions help researchers monitor the patients on a real-time basis and predict the side-effects of drugs.

Helping in early detection of diseases

Predictive analytics is helping companies in the pharmaceutical industry in the early detection of drug toxicity as well as improving the chances of patient survival. The algorithms used by predictive analytics helps in gaining detailed insights into patient data and deliver personalized care to the patient.

Our pharmaceutical industry experts help companies to manage their supply chains through specialized algorithms, tools and analytics models. Get in touch with them right away.

Providing real-time feedback

Today leveraging big data analytics solutions has become imperative for the pharmaceutical industry to reach out to their end-users in a better manner. Digital apps can help companies build relations with the target audience. The data collected on these apps are linked to various verticals of the pharmaceutical and healthcare industry which provides primary data on patient compliance and instant feedback on the health of patients.

Allowing doctor-pharma collaboration

One way in which big data analytics is making improvements in the pharmaceutical industry is by predicting the best treatments for individual patients. It can help in looking through data faster than humans and find the interventions likely to cause the most significant advantages for ill patients and their caregivers. With help from big data analytics, pharmaceutical companies can reach out to physicians treating patients that fit appropriate criteria and advise on how a certain medication could and should fit within a person’s treatment plan. Also, some physicians collect real-time data about whether treatments have intended effects, especially when their patients use Internet of Things (IoT) enabled wearables.

Wonder how big data analytics solutions can help you improve ROI significantly? Request for more information below.

manufacturing analytics

Manufacturing Analytics: Key to Drive Significant Improvements Across Business Operations

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.

Our manufacturing data analytics solution can help you understand the cost and efficiency of your product lifecycle. Request a FREE proposal now to gain better insights into our portfolio of services.

manufacturing analytics

Benefits of Manufacturing Analytics

Decrease downtime

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.

Quantzig helps companies to develop effective strategies that can consistently guide them gauge their own need for repairs. Request a FREE demo below to know more.

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

Why Quantzig?

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.

Want to learn more about how manufacturing analytics can help you predict maintenance issues and prevent breakdowns? Request for more information now!!

oil and gas industry

The Oil and Gas Industry: Witnessing a New Era with Digital Technologies

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?

Data management

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

data integration

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.

Our analytics experts help oil and gas companies in the effective integration and analysis of operational data for proactive decision making. Get in touch with them right away.

big data solutions

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.

Quantzig’s big data and analytics solutions help  leadingcompanies to successfully improve marketing ROI, customer relations, and devise the most profitable customer segmentation strategies. Request a FREE demo below to gain in-depth insights into our portfolio of advanced analytics solutions.

big data

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.

Want to learn more about the impact of digital transformation on the oil and gas industry? Request for more information below.

chemical industry

How is Industry 4.0 Transforming the Chemical Industry?

With the rise of the fourth industrial revolution (Industry 4.0) is growing the opportunities for the chemical industry. Industry 4.0 has the potential to transform the chemical industry by streamlining operations and promoting strategic growth. Moreover, Industry 4.0 has also given rise to technological advancements which are relevant to the chemical industry such as the Internet of Things (IoT), additive manufacturing, advanced analytics, artificial intelligence, and robotics. These technologies can be efficiently integrated with core conversion and marketing processes to digitally transform operations and enable smart supply chains and factories as well as new business models.

Our advanced analytics solutions help chemical manufacturing companies to shift from trial and error based approaches to modeled outcomes to digitize the material-selection process. Request a FREE proposal to gain better insights into our portfolio of advanced analytics solutions.

In this article, Quantzig’s chemical industry experts have assessed key applications of industry 4.0 in the chemical manufacturing sector. Also, they have listed ways in which industry 4.0 could help chemical companies to achieve strategic imperatives, specifically in the areas of business operations and business growth.

Role of Industry 4.0 in Transforming Chemical Industry

Improve business operations

Industry 4.0 is helping the chemical industry in improving business operations in two ways i.e., byimproving productivity and reducing risk. Smart techniques introduced by industry 4.0 such as predictive asset management, process control, and production simulations can help chemical companies in improving productivity. Also, it helps in planning supply chains, predicting demand patterns and aligning manufacturing operations.

Advanced technologies such as the IoT could allow chemicals manufacturers to improve their existing products and deliver better customer service. Want to know how? Get in touch with our experts now.

Generate new revenue and drive growth

Industry 4.0 has helped chemical industry players in driving business growth by developing new offerings and improving existing ones through research and development (R&D) of advanced materials and specialty products. Also, digital technologies enable companies in the chemical industry to integrate with customers’ operations and customize products, extend their products with information and services in a way that allows them to develop new business models.

Quantzig’s analytics solutions help chemicals companies to gain better visibility into supply chains and provide real-time recommendations to optimize the operations. Request a FREE demo to know more.

Data management

Data management includes all the activities associated with the collection, aggregation, storage, and processing of data. Companies in the chemical industry have been struggling with the fact that their data is stored in different systems. For example, financial, sales, and marketing data is stored in one system; operations, production, and manufacturing in different; and research and development and engineering in another. Industry 4.0 can be helpful in combining all these data and can offer a holistic view of the organization.

Industry 4.0 driven capabilities can help chemical manufacturers in driving productivity and maximizing profitability. Wonder how? Request for more information.

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