Vuelitics - Data driven company helping our clients to reduce the time for market and technology adaptation by making strategic operational decisions for Business through data science. Be it enterprise-wide CEO-led initiatives or line-of-business driven Business Intelligence needs. - https://vuelitics.com/
Don't wanna be here? Send us removal request.
Link
Business Analytics is ● analyzing and transforming data into useful information by the use of math and statistics; ● discover and predict the trends and results, and ● fundamentally, make smarter, data-driven business decisions.
It uses predictive analysis, data mining, and statistical analysis to extract valuable insights from the data. Business Analytics Techniques Business analytics techniques provide solutions to everything a company needs to make informed decisions – from what is happening in the company to what panacea to apply for optimizing the business functions and how to positively impact the business goals. 1. Descriptive Analytics The primary, yet the simplest technique entails decoding the data into understandable information. Its purpose is to outline the discoveries and help one understand what is happening in the business. Businesses use descriptive statistics on the existing data to discover the strengths and weaknesses to plan and strategize.
The two main approaches are data aggregation and data mining. Companies mine historical data to study consumer behaviors and engagements with their businesses for service improvement, targeted marketing, upselling, etc. read more...
2 notes
·
View notes
Link
What is Business Analytics? Business analytics is a subset of business intelligence and data management solutions. It entails data science insights like data mining, predictive analytics, and statistical analysis to interpret and transform data into valuable information, identify, and foresee outcomes to make informed, data-driven business decisions.
The business data analytics from the tools are interrelated, and each of them offers a distinct insight. And with the right business analytics tools, big data can yield deeper insights into the business.
The analytical techniques in business include:
● Data Aggregation: Data needs to be collected, filtered, and organized prior to analysis, to fetch valuable insights.
● Data Mining: Data mining for business analytics browses through huge datasets using machine learning, databases, and statistics to identify patterns, trends, and build relationships.
● Sequence Identification and Association: this technique is characterized by the identification of expected actions that are performed in liaison with other actions sequentially.
● Text Mining: this technique rummages and prepares huge, unstructured text datasets for qualitative and quantitative analysis.
● Forecasting: It studies past data from a specific time to make calculated predictive estimates to determine future events or trends.
● Predictive Analytics: Predictive business analytics entails statistical techniques to create predictive models, that extract information from datasets, identify trends, and offer a predictable score for a series of organizational outcomes.
● Optimization: Ince the trends have been figured and forecasts have been made, businesses can involve simulation techniques to test and confirm working scenarios.
● Data Visualization: It offers visual representations like maps, charts, and graphs for simple and straightforward data analysis.
The mandatory aspects of business analytics are classified into essentials: descriptive analytics, which examines historical data to identify how a unit will react to a set of variables; predictive analytics, which looks at historical data from descriptive analytics to understand the probability of specific future outcomes; or prescriptive analytics, the amalgam of the descriptive analytics process, that provides details on what happened, and predictive analytics process, that provides information on what might happen in the future, providing a detailed process by which users can foresee what will happen when it will happen, and why it will happen.
The latest, sophisticated business analytics software platforms and solutions are built to leverage and break down the large datasets that businesses meet and it can be totally used for optimal business operations. Takeaway: Business analytics is a powerful tool for organizations that are aspiring to grow and increase their business operations and services. At an individual level, a better and detailed understanding of data will not only lead to informed decision-making, but also provide deeper insights that will bag recognition in the workplace.
Leveraging data analytics to run an organization is a very effective way. With data as a backup to support the business level decisions, the meeting will not only turn influential but also successful.
#dataanalytics#insights#business#business consultation#businessconsultant#usa#texas#bigdata#technology
2 notes
·
View notes
Link
Investing in business intelligence technologies will help you stay ahead of your competitors!
It helps the executive cadre to make informed decisions for their business. Gone are the days when businesses were on the lookout for accumulation and data storage. The situation has recast into accumulating relevant and quality data. With new technologies seeing their genesis often, data storage costs have really become a thing.
IT departments that used to run complex reports to break stored data can now crunch big data with meaningful insights using business intelligence tools. Even better, it has transformed into providing businesses with customization that can seamlessly fit with the business processes and efficient for the decision-makers to analyze and decide. Data Quality Management (DQM) (DQM) refers to a business proposition that is the synergy of the right people, technologies, and processes with a common goal of enhancing quality data over quantity. Quashing data blindness is a vital part of managing data. Data Discovery It is the process of collecting data from multiple silos and databases, merging it into a single source, so it can be easily and rapidly evaluated. It is done through advanced analytics and visual navigation of data that stretches beyond conventional static reports. Artificial Intelligence Artificial intelligence (AI) uses computer systems to simulate different attributes of human intelligence, like learning, problem-solving, decision making. The sophistication to model off human intelligence and fetch insightful data with reports makes it an important thing in business data analytics. Predictive and Prescriptive Analytics Tools Predictive analytics interprets information from the existing data, and predicts possibilities, while prescriptive analytics determines what decisions and measures should be taken to attain certain business goals, based on those predicted possibilities. Connected Clouds Businesses are already using some sort of cloud services. Owing to the efficiency and innumerable possibilities that the cloud has in store, organizations are flocking towards the cloud to get in-depth business insights and analytics. Besides, multi-cloud serves as a panacea to shield data loss. The benefits of cloud-based services include:
● Ability to access information anywhere, anytime. ● Ability and time to implement and deploy solutions. ● Low overhead and easy scalability. ● Competitive edge through reliable access to democratized data. Ad Hoc Reporting With Ad hoc business intelligence reporting, companies can gain access to detailed and direct reports. It makes daily decision-making straightforward. It significantly lessens the workload and makes creating on-spot reports relatively simple. It enables businesses to filter information from the cumbersome data.
#data security#data#analytics#datainsights#data recovery#consulting#business#businessintelligence#marketing#business insights
2 notes
·
View notes
Link
Business Analytics is ● analyzing and transforming data into useful information by the use of math and statistics; ● discover and predict the trends and results, and ● fundamentally, make smarter, data-driven business decisions.
It uses predictive analysis, data mining, and statistical analysis to extract valuable insights from the data. Business Analytics Techniques Business analytics techniques provide solutions to everything a company needs to make informed decisions – from what is happening in the company to what panacea to apply for optimizing the business functions and how to positively impact the business goals. 1. Descriptive Analytics The primary, yet the simplest technique entails decoding the data into understandable information. Its purpose is to outline the discoveries and help one understand what is happening in the business. Businesses use descriptive statistics on the existing data to discover the strengths and weaknesses to plan and strategize.
The two main approaches are data aggregation and data mining. Companies mine historical data to study consumer behaviors and engagements with their businesses for service improvement, targeted marketing, upselling, etc.
2. Diagnostic Analytics It helps to diagnose why something happened in the past through data examination, data discovery, data mining, and correlations. It digs to the roots of the data to understand why the events occurred and ascertain the factors contributing to the outcome. Probability, feasibility, and outcome distribution are used for the analysis.
For example, diagnostic business data analytics will help with reasons for increase or decrease in sales in that year, however with limited actionable insights. It will help you understand the connection and sequence. 3. Predictive Analytics Predictive analytics collects information and uses it to predict future outcomes. It predicts the probability of an event to occur in the future. It builds on the preceding descriptive analytics phase to extract the likelihood of the outcomes.
The specialty of predictive analytics is to create models to foretell future data. It is characterized by machine learning algorithms for analyzing and testing data.
For example, predictive analytics is used to determine the opinions posted on social media by common people and deduce their sentiment. 4. Prescriptive Analytics Prescriptive analytics along with testing and a few other techniques are used to decide which outcome will produce the best results in a series of situations. It optimizes functions to produce the desired outcome while ensuring key performance metrics are used in the process.
For example, while booking a cab online the application uses GPS to locate the closest driver to your location.
#data analysis#business intelligence#business#datainsights#business insights#data#analyics#businessconsulting#consulting
1 note
·
View note
Text
Vuelitics-Big Data Analytics & Business Intelligence Company | DE
Vuelitics-Top business intelligence company in the Dover, Delaware, USA. We provide big data analytics solutions, advanced data analytics.
vuelitics's insight:
Vuelitics - Data driven company helping our clients to reduce the time for market and technology adaptation by making strategic operational decisions for Business through data science. Be it enterprise-wide CEO-led initiatives or line-of-business driven Business Intelligence needs, Vuelitics is equally adept at handling both. We help our customers using their data to discover and act: what is happening; why is it happening; what will happen and why; what should be done. https://vuelitics.com/
Adress: 8 The Green, Suite # 4539 Dover DE 19901, Delaware, USA. LinkedIn - https://www.linkedin.com/in/vuelitics-data-driven-insights/
Pinterest - https://www.pinterest.com/vueliticsanalytics/
Medium - https://medium.com/@vueliticsanalytics
Tumblr - https://vuelitics.tumblr.com/
Reddit - https://www.reddit.com/user/Vuelitics
Our key strengths:
Data Analysis and Problem Solving.
Specific industry knowledge.
Global delivery skills with Strong talent pool.
Robust infrastructure with internationally certified security controls.
Expertise in popular data technology platforms.
38 notes
·
View notes
Text
HOW DO YOU CREATE A MARKET BASKET ANALYSIS IN TABLEAU
Tableau is a premium BI tool, that delivers powerful insights about your data through in-depth analysis and vivid visualizations. It is a unique software compared to its competitors as it provides high-quality analytics and visualizations allowing its users to derive the maximum insights from their data. In this article, we will go through every step in setting up a market basket analysis in tableau.
WHAT IS A MARKET BASKET ANALYSIS?
It is a commonly used technique among retailers to gain knowledge about the purchasing behavior of their clients. Simply put, the technique helps users to understand the correlation between two different products, allowing retailers to optimally arrange products in their outlets. The “People who bought this item also bought this” section is based upon this analysis. Thus, retailers can maximize their revenue by pairing up products and discounting the price based upon this technique.
Let us go through the setting up of a simple analysis in Tableau.
– Let us assume that we have a database of a grocery store with all relevant data like orders, categories, returns, products, etc.,
– The order has associated data like order ID and order date while the product has relevant data like category and sub-category
– Go to the data source and do a self join with orders based upon the order ID.
– We will do the market analysis on categories and you can choose any relationship between them for the time being
– Now move to the sheets and drag the category from products and drop it on columns
– Then drag the category from self-join and drop it on rows
– Now drag the order ID from Order to text box on Marks.
– Then ensure that the count of the order ID is displayed by selecting count from the measure dropdown
– Drag the order ID tag and drop it on color to have a finer view of the analyzed data. You can also change the shape of the view based upon convenience
– You can also have a simpler view by changing the relationship we fixed on the join tab
Thus, you have a comprehensive picture of the correlation between different products that the retailers can use to their advantage.
Thus, gain powerful insights about customer behavior using this technique to accelerate revenue generation with optimum effort.
#data#analysis#analytics#tableau#bi consultants#biconsultants#power bi consulting#powerbiconsulting#business intelligence consulting#businessintelligence#business insider#business#advanced data analytics#advanceddataanalytics#data analytics#advanced
37 notes
·
View notes
Photo

HOW DO YOU CREATE A MARKET BASKET ANALYSIS IN TABLEAU - By Vuelitics. Tableau is a premium BI tool, that delivers powerful insights about your data through in-depth analysis and vivid visualizations. It is a unique software compared to its competitors as it provides high-quality analytics and visualizations allowing its users to derive the maximum insights from their data. - Setting up of a simple analysis in Tableau.
#market basket analysis#marketbasketanalysis#tableau#bi tools#business#analytics#analysis#datavisualization#data analysis#databreach#information#data analytics strategies#data analytics services#data analytics#dataanalytics
33 notes
·
View notes
Photo
KNOW WHY DATA ANALYTICS IS IMPORTANT FOR ANY BUSINESS. The Covid-19 situation has disrupted the business environment for the worst and many businesses are at their wit’s end about their future. An advanced data solutions provider like Vuelitics can help executives and managers get the much-needed clarity about their current business and prepare for the future. Most businesses are online nowadays and the pandemic situation has forced others to do the same. Thus, data analytics has become very relevant, and in this article, we will discuss some of the methods and the importance of data analytics. - WHAT DATA ARE WE TALKING ABOUT? - DATA ANALYTICS STRATEGIES. - BENEFITS OF DATA ANALYTICS. - WHY SHOULD YOU CHOOSE VUELITICS? - CONCLUSION.
#data#data analysis#dataanalytics#data services#analytics#business#marketing#analys#predictiveprogramming#predictive maintenance#predictive
33 notes
·
View notes
Text
WHY DATA ANALYTICS IS IMPORTANT FOR ANY BUSINESS
WHY DATA ANALYTICS IS IMPORTANT FOR ANY BUSINESS.
The Covid-19 situation has disrupted the business environment for the worst and many businesses are at their wit’s end about their future. An advanced data solutions provider like Vuelitics can help executives and managers get the much-needed clarity about their current business and prepare for the future. Most businesses are online nowadays and the pandemic situation has forced others to do the same. Thus, data analytics has become very relevant, and in this article, we will discuss some of the methods and the importance of data analytics.
WHAT DATA ARE WE TALKING ABOUT?
Data solution providers like Vuelitics are primarily concerned with data analytics in marketing and analyse the business website for valuable insights. For example, the bounce rate can gauge the interest your website generates among your audience as a higher bounce rate is not desirable. Similarly, we provide deep insights into other relevant data like demographics and conversion rates. Vuelitics is proficient in handling huge amounts of such data quickly with accuracy by employing state of the art tools such as Qlikview, Qliksense, and PowerBI. Thus, data analytics can offer you data related to client behavior, allowing you to customize your product.
DATA ANALYTICS STRATEGIES
Vuelitics primarily conducts two kinds of analysis which are qualitative and quantitative analysis. As the words imply qualitative methods involve figuring out the reasons for the business performance and quantitative methods involve gathering numbers validating the reasons. However, Vuelitics also deals with various other kinds of strategies like text analysis, statistical analysis, and diagnostic analysis. Graphical analytics using tools like Qlikview offer a visual perspective to businesses, helping them to easily understand complex statistics. Vuelitics specializes in predictive analysis by employing machine learning to predict patterns and trends and prescriptive analysis by suggesting numerous plans for the future.
BENEFITS OF DATA ANALYTICS
Data analytics can be the perfect tool for this pandemic as businesses can carefully analyse their customer behaviour and optimize their customer satisfaction. Also, millennials today expect carefully curated content and product that can be customized according to the data. High-quality data solutions can also help organizations prevent security threats and cyber-attacks. It also helps businesses to compete better as they can continuously improve their product by studying user data and feedback. Analytics tools such as Power BI, Qliksense, and Qlikview help businesses to streamline their production pipeline thereby ensuring optimum customer experience.
WHY SHOULD YOU CHOOSE VUELITICS?
Vuelitics mission is to integrate all the data points available in the client’s business using its high-performance data analytics tools and offer a comprehensive vision for business development. We specialize in guiding the business in the most profitable directions fostering optimum growth for the business. We have a systematic approach for every business that starts with a deep analysis of the business to identify the objectives and wants of the business. Equipped with the best tools in BI like Qlikview, Qliksense, and Power BI, we then chart a path to achieve those objectives and monitor the results for continuous development.
CONCLUSION: Data analytics in business is going through tremendous changes and the benefits are adding up with each successive change. New trends are emerging that can effectively cut losses and accelerate profits for any business. Thus businesses with a data solution partner like Vuelitics definitely have a competitive edge over their peers.
#data#data security#data analysis#datascientist#information#business#businessintelligence#predictive analytics#predictive#predictive maintenance#predictiveprogramming#predictive policing#analytics#consultants#biconsultants#power bi#powerbi#advanced data analytics#advanceddataanalytics
46 notes
·
View notes