Haneen Alansari Analytics in business blog.

How Big Data Advances Ecommerce ? Big Data is now altering how organizations evaluate client conduct, and that is set to proceed into what's to come. In any case, how enormous of an effect will Big Data have on computerized showcasing, and by what means will it influence our advanced advertising methodologies? Measure of Data The measure of Data advertisers now approach has detonated in the course of recent years – particularly as cell phones have taken off. IBM has expressed that 90% of the world's Data was made in the previous 2 years, and this will just proceed as we have an ever increasing number of associated gadgets we use in our regular day to day existences. Social Conversions Gartner has said that there are as of now 5.5 million "web of things", or IoT, gadgets that are associated each day. This incorporates TVs, coolers, indoor regulators, and everything in the middle. This Data is put away and can be broke down by advertisers to ju

Web Analytics Implementation In digital marketing, Implementation is an essential in analytics because that is the actual transformation of the data into actionable information. Every business is eager to implement business analytics to help them to increase profit and of course to reduce costs. It seems not easy to set up a web analytics program one page. So the most important element is to find insights into the organization. Most of these insight that must business gain it and work with it is the following. ·          Define the Objectives The objectives of the goals set to accurate and precisely on how the company achieved . Also, determent the site performance metrics. ·          Evaluate the Site: Assess the website like the its customer interface, architecture and transaction methods. ·          Create a Classification Report for the site: Using draft reports that segments the content, requirements, and visitors to develop a formal implementation plan.

Web Analytics Implementation   Every business is eager to implement business analytics to help them to increase profit and of course to reduce costs. Web analytics implementation aims to ensure that business most be accurate and complete to be collected to understand when consumers visit the website.   To Configure which kind of variables and data are used to create the reports on which your business relies for information.   In digital marketing its hard to keep business goals for a clear and informed analysis. Implementation an analysis to match with business strategy by the following: Testing:   In digital marketing experimentation the content to understand which approach or strategy works to better accomplish for business goals. Goals: The objectives of the goals set to accurate and precisely on how the business achieved.   Key Performance Indicators: The variables that repre

Data Monetization strategy in Business   Data monetization is all about selling the data which in turn is about revealing certain characteristics .It depends on how individual company approaches the concept to the data monetization no matter the company or their individual approach.An organization can play only one role in data monetization. It can either be a consumer of the data, an aggregator of the data or the creator of the new data. By understanding which role fits the organization best, one will be able to find the ways to monetize the data. Finally,Every company will approach data monetization differently, but gathering a variety of ideas from academia, tech analysts, and leading practitioners. Data monetization can be about selling data. Most of the time, monetization is less direct: making a process run more efficiently, incentivizing certain types of behavior, or revealing the true value of an asset. It is increasingly becoming a significant  for business

Data Monetization strategy in Business   D ata Monetization is a way of process of actively generating value from a company’s data inventory. Data monetization strategy actively looks to extract potential value through three essential factors: Aggregating and Analyzing                                          Organization look to drive incremental revenue by aggregating multiple data sources and conducting deep analyses through data science. Therefor, The resulting models are then used to drive changes in the decision-making process for operational, sales, and marketing. While the Ownership of value is retained and protected, but the cost of value generation is the highest of the three models. Crowdsourced Data Insights Crowdsourced data insights are based on the driving value from the crowd; data is supplied to the crowd for analyses that produce specific actionable outcomes. For instance, Kaggle.com is a data prediction competition platform that

Data Monetization strategy in Business   Data monetization  is form of monetization, is generating profit from available data sources or real time streamed data by instituting the discovery, capture, storage, dissemination ,analysis, and use of that data .A new report released by Economist finds that organizations are actively monetizing their data. By 60% are already generating revenue from their data. while 83% say data is used to make existing products and services more profitable. The ownership of rich measures of information is not special in this day and age. Without a doubt, information itself is progressively an item. The capacity to adapt information viably can be a wellspring of upper hand in the computerized economy. Organizations can adopt three strategies to adapting their information: (1) enhancing inward business procedures and choices (2) wrapping data around center items and administrations (3) pitching data offerings to

Data visualization Conclusion So I thought it is interesting that data visualization can absorb information in new constructive ways. This can be a great deal since the ability to visualize data can help to improve people product or test its consumer need. Data visualization can also be a benefit to the rest of your staff, not just the higher up employees. Data Visualization tools give you the capability to sift through the data and see it with new eyes. Data visualization is significant because of the way the human brain processes the information, using graphs or charts to visualize large amounts of complex data is easier than poring over reports or spreadsheets. Also, data visualization is a quick, way to convey concepts in a universal manner and client can experiment with different scenarios by making slight adjustments. Also, data visualization is an effective way to analyze large amounts of data to identify correlations, trends, outliers, patterns,

Data visualization is the graphical presentation of abstract information for two purposes: the making of sense (also called data analysis) and communication. Important stories that live in our data and the visualization of data is a powerful means to discover and understand these stories, and then present them to others. Information is abstract in that it describes things that are not physical. The statistical information is abstract. Whether it is sales, sickness, athletic performance, or anything else, even if it does not belong to the physical world, we can still show it visually, but for this, we must find a way to shape what has none. This translation of the abstract into physical attributes of vision (length, position, size, shape and color, to name a few) can only be successful if we understand a little about visual perception and cognition. In other words, to visualize the data effectively, we must follow the design principles that derive from an understanding of

Data visualization Introduction   Data visualization is a general term that describes any effort to help people understand the importance of the data by placing them in a visual context. Patterns, trends, and correlations that may go undetected in text-based data can be more easily exposed and recognized with data visualization software. The visualization of analytics results, through dashboards, provides the means for decision makers within a company to quickly grasp the meaning of the information. Companies should think about how they want the information layer to be presented before embarking into an analytics project. The information layer should be directly correlated to the business objectives. Also, it should be flexible to add new requirements. Companies should consider utilizing the advances in visualization techniques when planning a dashboard. This includes the ability to see the