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Category: Business Intelligence
What is Natural Language Processing and Why Do I Need it in My Advanced Analytics Solution?
What is Natural Language Processing (NLP)?
Natural Language Processing utilizes artificial intelligence to translate computer code and language into real world, human language. While the goal is to simplify human interaction with computers, NLP is a complex mix of computational linguistics and computer science. When a business is considering an augmented analytics solution that leverages natural language processing, it need not concern itself with the complicated underpinning of code and design, but should rather consider what NLP can do for its users and for its business results.
What Determines the Success of a Citizen Data Scientist Initiative?
By now, every wise business team has acknowledged the advent of digital transformation and the transformation of business users into Citizen Data Scientists. But acknowledging the reality and enabling that reality within the walls of an enterprise are two very different things. Where many businesses fail in implementing the Citizen Data Scientist initiative, it is typical to find that the business has simply decided to deploy the strategy without much planning or culture change. Without understanding the shift in workflow, responsibilities and how the use of data will change the enterprise, it is unlikely that the business will succeed in its Citizen Data Scientist initiative.
Here’s How Mobile BI Encourages User Adoption and TCO!
Businesses that invest in business intelligence solutions expect to achieve results, become more competitive and improve productivity, but these businesses often fail to understand the need for Mobile BI. Mobile business intelligence should provide all the features and search capability a user needs to perform tasks and get information while on the road, working remotely or visiting a client, partner or regional office.
Combine Traditional BI with Modern BI and Analytics to Improve User Adoption and Gain Advantage!
The world-renowned technology research firm, Gartner, predicts that, ‘through 2024, 50% of organizations will adopt modern data quality solutions to better support their digital business initiatives’. As businesses consider the options for data analytics, it is important to understand the impact of solution selection.
Going Beyond the Numbers with SmartenApps for Tally!
The Tally® ERP Solution and its latest TallyPrime offering are popular accounting and finance related suite of modules that provides support for invoicing and accounting, inventory management, reports, credit and cash flow management, banking, cost control and analysis, payroll management and other finance-related activities.
Our Partner is a healthcare service provider in the United States providing a web-based, patient-centric, healthcare management solution and workflow solutions to increase operational efficiency and reduce costs for its hospitals and healthcare facility Clients. Since 1999, the Partner has provided services to the durable medical equipment and supply market with solutions that benefit many healthcare organizations and clinics in the U.S.
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Drive User Adoption with Embedded BI and Single Sign-On Convenience!
All of your business users have a favorite software application – an app they value because it helps them do their job more easily, or helps them get crucial information. These are the applications they have learned and they are used to leveraging them on a day-to-day basis to perform tasks. When you introduce augmented analytics into your business environment, one of the most critical factors is whether you can expect user adoption. Finding and implementing the right augmented analytics solution is just the first step. If you can’t get your users to USE the application, your return on investment (ROI) will be poor and your total cost of ownership (TCO) will be high.
1. Missing Data – Why does it matter so much?
Ever worked upon an analytical project and noticed the presence of blank or NAN or undefined values in the records representing the data and being in need of correctly dealing with them? This might be a routine situation while working with real world data. It becomes a crucial step to execute fair technique to handle these missing values after understanding the analysis required from the data as often data for one party can be a noise to another party. Data can be missing owing to corrupt data, incomplete data extraction process, data entry errors or simply the data is rare and is actually missing! But handling such data is of great challenge in order to make right decisions and generate robust predictive models or reports. This article sums up key steps to handle missing values using Smarten Augmented Analytics and further explains its utility from the Employee Salary Prediction dataset.
