Tag: Data Science

data and analytics

Weekly Round-up: A Storyboard on the Importance of Data and Analytics for Businesses

LONDON: Quantzig, a leading analytics services provider, has announced the release of their new storyboard on the importance of data and analytics for businesses. Each of these downloadable articles explains how data and analytics solutions can help companies to make smart decisions, improve customer satisfaction, decrease e operational expenditure, reduce risks, and enhance fraud management.

Business leaders across industries are increasingly adopting big data analytics and data visualization techniques to improve their business operations. However, many organizations still seem to think of analytics as a quick fix for their business needs and investing in data and analytics is just the beginning of their journey. But to achieve business goals, it is high time for businesses to leverage data and analytics solutions that can help them boost transparency and enhance their approach towards data-driven decision making.

Quantzig’s data and analytics solutions have helped companies with the right data visualization techniques, capabilities, and frameworks to handle the volume, variety, and velocity of data to make informed business decisions while ensuring information privacy and security. Below, we have summarized some of Quantzig’s free resources and have also highlighted ways in which data and analytics solutions have helped businesses to gain a leading edge in today’s competitive business scenario.

Our data and analytics solutions help companies to make proactive business decisions and pre-emptive planning. Request a free proposal to gain better insights.

#1: How can analytics solutions transform business models? A successful business model is not just about completing a business plan or determining which product or service to pursue. It is about mapping out the strategy to create ongoing value for customers. But you must be wondering where to start. This free resource by Quantzig can be your key to success. It gives a detailed overview of how companies can reshape their business models by leveraging data and analytics solutions. Also, it unveils five secrets that can help companies identify and capitalize on new business opportunities.










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#2: What are the top AI and analytics trends in 2019? Analyzing and optimizing the customer experience is the bedrock of successful digital transformation in 2019. Data and analytics capabilities with minimal manual efforts have become the hallmark of all business intelligence solutions. Artificial intelligence (AI) and machine learning technologies are transforming businesses and organizations have become highly dependent on automated data-analysis capabilities. This free resource by Quantzig uncovers some of the top AI and analytics trends that took off within corporate boardrooms but will continue to proliferate across different layers of business operations in 2019 and beyond.






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#3: What are the key steps to build an analytics-driven organization? Companies across industries agree that the capacity for data and analytics is becoming very crucial to their basic viability. Therefore, they need to be prepared for the future when data and analytics are going to be both important and integrated at all levels of organizational decision-making. It has become imperative for businesses to exploit available data in order to maximize profits. However, when it comes to extracting business value from data, most of the companies fail miserably. Quantzig’s free resource uncovers a few important steps that can help organizations to improve transparency, enhance business efficiency, and boost overall business performance. Download the free resource now to know more.







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All About Data Science and Its Growing Importance for Businesses

With the world entering the era of big data, the need for its storage has also increased. This was a cause of concern for businesses until 2010 and their focus was centered around building solutions and frameworks to store the huge data volumes. Today Hadoop and other frameworks have successfully solved the issue of storage and the focus of businesses have shifted to the processing of this data- Data Science is the secret sauce here. The future of artificial intelligence lies in Data Science. Therefore, it is very crucial to understand what is data science and how can it add premium value to your business.

Are you wondering how to identify order and patterns in data? Data science may hold the key to success. Get in touch with our data scientists to know how identifying patterns, as well as spotting trends, can help the bottom line of your business. 

What is Data Science?

Data Science is a blend of various algorithms, tools, and machine learning principles that help unveil hidden patterns from the raw data. Data Science is a more forward-looking approach that analyzes the past or current data and predicts the future outcome that further helps in making informed decisions. It has the potential to answer open-ended questions such as “what” and “how” scenarios. Data scientists need to master the full spectrum of the data science life cycle in order to uncover useful intelligence for their organizations. There is a need for a certain level of flexibility and understanding to maximize outcomes at each phase of the data science process.

Data science is an interdisciplinary field that deals with systems and processes, that are used to extract insights or knowledge from huge amounts of data. Data extracted can be structured or unstructured. Data science process is a continuation of data analysis fields that includes predictive analysis, statistics, and data mining. Data science visualization is a vast field that uses a lot of techniques and theories that are a part of other fields like mathematics, information science, chemometrics, statics, and computer science. Some of the methods used in data science include:

  • Probability models
  • Machine learning
  • Signal processing
  • Data mining
  • Statistical learning
  • Database
  • Data engineering
  • Visualization
  • Pattern recognition and learning
  • Uncertainty modeling
  • Computer programming

With the ongoing technological advancements, many aspects of data science are gaining immense importance, especially big data. Data science is not just limited to big data, which in itself is a vast field because big data solutions are more focused on pre-processing and organizing the data rather than analyzing it.

Want to know how data-driven techniques and data analytics can help you solve business-related problems. Request for more information here.

What is the difference between data science and machine learning? 

Difference #1: Data science tools create insights from data dealing with all real-world complexities. This comprises tasks like extracting data and understanding requirement etc. Whereas, machine learning classifies or predicts outcome accurately for new data point by learning patterns from historical data using mathematical models.

Difference #2: In data analytics, most of the input data is generated as human consumable data which is to be analyzed or read by humans like images or tabular data whereas input data for machine learning are transformed specifically for algorithms used.

Difference #3: Data analytics and science require domain expertise, strong SQL skills, ETL and data profiling skills whereas machine learning requires a strong understanding of mathematics, data wrangling with SQL model specific visualization.

Quantzig’s analytics solutions offer clients with the right big data technologies, tools, capabilities, and frameworks to handle the variety, volume, and velocity of data to help organizations make informed business decisions while ensuring information security and privacy. Request a free proposal to know more about our portfolio of services.

What are the benefits of data science?

Benefit #1: Helps to understand the customers efficiently

Data science tools help brands to understand and analyze their customers in a much empowered and enhanced manner. Customers are the base and soul of any brand and have a very important role to play in the success and failure of any brand. With the help of data visualization, brands can connect with their customers in a personalized manner. Furthermore, this can ensure better brand engagement and power.

Benefit #2: Improves the brand’s engagement with the customers

Data science is gaining huge attention because it enables brands to communicate their story in an engaging and effective manner. When companies and brands use this data in a comprehensive way, they can share their story more effectively with their target audience, thereby creating better brand engagement. After all, nothing better than human emotions can connect with consumers more effectively.

Benefit #3: Assists in complex problem solving

Data science is a field that is constantly evolving and growing. With so many data science tools being developed, almost every day, big data is assisting organizations and brands to solve complex problems in human resource, IT, and resource management in a strategic manner. This means better use of both material and non-material resources.

Benefit #4: Findings of data science is applicable to every industry

This is one of the most important aspects of data science that its results and findings are applicable to any sector such as healthcare, travel, and education. Understanding the true and appropriate implications of data science can help sectors in analyzing and addressing their challenges in an effective fashion.

Benefit #5: Aid in mitigating challenges of demand and sustainable future

Data analyticsfocuses on the use of general methods without modifying its application, irrespective of the domain. This approach is quite different from traditional statistics that generally tend to focus on offering solutions specific to particular domains or sectors. Today, data analytics and science has far-reaching implications. With the aid of speech recognition, machine translation data science is helping almost every industry to mitigate challenges of demand as well as paving way for the sustainable future.

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3 Ways Predictive Analytics Solutions Can Help Businesses Derive Successful Outcomes

With the shifting key values of every industry from customer-focused to customer-centric, there is an immense growth in data and information. This has changed customer dynamics and as a result, every business is facing numerous challenges such as market uncertainties, driving efficiency, and effectiveness in their marketing productivity, immense competition, customer demands, fraud detection, and risk management.

Many businesses across all industries, in order to cater customer demands, are trying to utilize the data that their customers leave behind while interacting with the company. Harnessing this pool of data can offer several benefits to organizations. However, many companies still have not realized the importance of data mining and have not gone beyond gathering and storing their data. Although it is difficult to deal with an unstructured set of data by leveraging predictive analytics solutions businesses can fetch optimum results from such data. 

At Quantzig, we understand the impact that predictive analytics solutions can have on your business. And to help companies derive actionable insights from large and complex data sets, our team of experts has highlighted three important ways in which predictive analytics solutions can help in managing large volumes of data and setting up analytical frameworks to derive real-time insights that facilitate more informed and wise decisions.



Why Data Governance Matters More than you Think?

The principle of “garbage in, garbage out” established the accuracy of computers, acknowledging a fundamental fact that computer errors are the result of faulty human inputs. The same principle can be applied to the field of data science, as inconsistent or incorrect data can draw an entirely misleading analysis of the problem. The use of data governance tools ensures an overall management of the availability, integrity, usability, and security of the data utilized in an enterprise. Although data governance is so critical for data management, many companies view it as a luxury tool and de-emphasize it.

Here are some of the reasons why companies should employ data governance to design effective data-driven marketing:

Ensuring Data Integrity

Data integrity issues cost organizations millions of dollars in direct and indirect cost. It is almost impossible to get reliable, consistent, and repeatable data without data governance. Data governance guarantees data integrity by protecting the data, irrespective of its formats. This data is then recorded, processed, and retained for future use.Free demo

Cost Savings

The end goal of every organization is to maximize its ROI. Properly defined core metrics, marketing exclusions, consumer segments, and attributes like CLV can not only help save the company money but also generate revenues. A strong data governance ensures superior data quality that reduces the likelihood of errors; thereby, contributing to indirect savings.

Solving Analysis and Reporting Issues

A problem with interpreting data results in a lack of clarity in the final analysis and reports. It usually happens when there is a lack of clarity while defining and interpreting various metrics. Data governance tools assist the managers in conveniently analyzing the data to derive an accurate analysis of the problem in hand.

Data Security

Today, companies store a lot of data which is sensitive in nature. When sensitive data such as financial information, customer information, contracts, and market intelligence gets compromised, companies can lose millions of dollars and face lawsuits. Data governance tools provide data security from both external and internal members by giving access to only authorized users.

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Enter Quantzig:

Today, managers have access to a large stream of data, and decision-making on the basis of gut-feeling, the rule of thumb, and guesswork are largely eliminated with the advent of data analytics.

“Without big data analytics, companies are blind and deaf, wandering out onto the web like a deer on a freeway,” said a leading data analytics expert from Quantzig.

For more than 14 years, we have assisted our clients across the globe with end-to-end data management and analytics services to leverage their data for prudent decision-making. Our firm has worked with 120+ clients, including 55+ Fortune 500 companies. At Quantzig, we firmly believe that the capabilities to harness maximum insights from the influx of continuous information around us is what will drive any organization’s competitive readiness and success. Our objective is to bring together the best combination of analysts and consultants to complement our clients with a shared need to discover and build those capabilities and drive continuous business excellence.

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Big Data Boosts Revenue and Profitability – Know How

There has been an exponential increase in the amount of real-time information generated from a variety of sources such as sensors, social media, previous transaction history, and mobile devices. In simple wFree demoords, this mammoth amount of data is termed as big data. Organizations can make use of big data and analytics to assess data and gain actionable insights that facilitate improvement, boost revenue, and drive profitability. To monetize the data available at your fingertips, businesses must leverage big data analytics to explore, experiment, and identify the value hidden in it. But how can data and analytics boost profitability, you ask? Here’s how.

Leverage Data Mining to Identify Patterns

Data mining techniques enable the organization to collect and organize useful data from different sources. In order to boost revenues and profitability, the management must leverage big data analytics to identify hidden patterns across the data generated by their consumers to gain actionable insights that help in strategic decision making. The identified data patterns can facilitate improvements and improve business performance by addressing the basic questions and pinpointing factors that drive consumers to purchase your product.

Experimentation Is the Key to Success

To ensure profitability, the data science team must have the liberty to explore and experiment to find data opportunities and gain valuable insights. It is essential to allow them to indulge in tactical work other than their routing analytical work to achieve the strategic business objectives, boost revenue and profitability. The data science analysts require additional resources in terms of time and monetary investment to identify new patterns and unearth new potential opportunities that help businesses gain a competitive edge in the market.

Monetizing big data is not a one-time activity but a continuous process that requires the business to constantly re-design their products based on the changes in the market and their customer needs. Organizations must put a proper big data analytics process in place and have a broad, long term vision to create value proposition; thereby, ensuring increment in sales revenue and profitability.

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