Domain-Specific Language Processing Mines Value From Unstructured Data

KDnuggets

Processing unstructured text data in real-time is challenging when applying NLP or NLU. Find out how an alternative, called Domain-Specific Language Processing, can mine valuable information from data by following your guidance and using the language of your business.

Knowledge Graph – A Powerful Data Science Technique to Mine Information from Text (with Python code)

Analytics Vidhya

Overview Knowledge graphs are one of the most fascinating concepts in data science Learn how to build a knowledge graph using text from Wikipedia. The post Knowledge Graph – A Powerful Data Science Technique to Mine Information from Text (with Python code) appeared first on Analytics Vidhya. NLP Python dependency trees graphs Natural language processing Natural Language Understanding Part of Speech python spaCy text data unstructured data

Sample-based analysis: A new approach for unstructured data management

IBM Big Data Hub

Introducing IBM StoredIQ Instascan for accelerated compliance and risk assessments. Read to learn more

Accelerating unstructured data compliance with a new approach: sampling

IBM Big Data Hub

The initial goal of sampling is to assess where the highest compliance risk areas are within your enterprise. Read blog to learn how IBM StoredIQ InstaScan accelerates this

Use Text Analytics Technologies To Handle Mountains Of Unstructured Data

Boris Evelson

Enterprises are sitting on mountains of unstructured data – 61% have more than 100 Tb and 12% have more than 5 Pb! Luckily there are mature technologies out there that can help. First, enterprise information architects should consider general purpose text analytics platforms. These are capable of handling most if not all text analytics use […].

Getting to the Future First: How Social Data is Transforming Trend Discovery

KDnuggets

Register now for this webinar, Sep 25 @ 12 PM ET, for a clear approach on how to apply machine learning language technology to massive, unstructured data sets in order to create predictive models of what may be the next “it” ingredient, color, flavor or pack size.

Creating a Big Data Platform Roadmap

Perficient Data & Analytics

One of the most frequently asked questions by our customers is the roadmap to deploying a Big Data Platform and becoming a truly data-driven enterprise. Just as you can’t build a house without a foundation, you can’t start down a big data path without first establishing groundwork for success. There are several key steps to prepare the organization to realize the benefits of a big data solution with both structured and unstructured data.

How to Gain Valuable Insights from Untapped Data Using AI

Perficient Data & Analytics

You probably know your organization needs to invest in artificial intelligence (AI) solutions to take advantage of the deluge of data that mobile and digital users are creating, but do you know why or how? LEGACY ANALYTICS METHODS AREN’T EQUIPPED TO PROCESS ALL DATA TYPES. The majority of data is unstructured (around 80%) which means it isn’t clearly defined or easily searchable the way that structured data is. LEVERAGE YOUR DATA WITH AI.

Is Your Data Management Infrastructure Modern Enough for IoT?

Hurwitz & Associates

IoT is supported by a variety of technologies – computer systems, networks, end user devices, software – but at the heart of IoT is the collection, storage, processing, and analysis of data. Data growth is nothing new, of course. The volume and even types of data relevant to doing business have been growing at an accelerated pace for some time, in great part as an outgrowth of web-based applications designed to reach consumers and support end user activities such as social media.

IoT 40

Cloudera - The ASEAN Appetite for Data in Motion

Corinium

The Big Data revolution has been surprisingly rapid. Even five years ago many companies were still asking the question, “What is Big Data?” Download the Report.

5 ways Data Analytics is a Game Changer for the Insurance Industry

DataFloq

We are in the age of ‘Big Data’ and while it is becoming a big business in the emerging technological world, let us understand and get a deeper insight on what Data Analysis basically is. . Big Data

Descriptive Statistics in Python for Understanding Your Machine Learning Data

DataFloq

Statistics has its own significance in data science, but it’s not the only thing which data scientists have to deal with. The commonly used way to address hidden characteristics within a data set is known as SCD. Data programming. Data mining. Data cleansing.

9 Formidable Big Data Analytics Tools for 2019

DataFloq

Typically big data is reckoned by its size, but experts also give credit to information technologies that are assisting analysts in analyzing huge clusters of unstructured data to make sense of data trends, patterns, and anomalies. Big Data

Rearchitecting Unstructured Storage

Nutanix

Unstructured data is typically comprised of data that is not easily searchable, including such formats as audio, video, and social media postings. It has an internal structure but is not structured via pre-defined data models and may be textual or non-textual, and human- or machine-generated. It is typically stored on file and object storage

NLP vs. NLU: from Understanding a Language to Its Processing

DataFloq

They both attempt to make sense of unstructured data, like language, as opposed to structured data like statistics, actions, etc. However, NLP and NLU are opposites of a lot of other data mining techniques.

IT 263

A Comprehensive Guide to Natural Language Generation

DataFloq

In its essence, it automatically generates narratives that describe, summarize or explain input structured data in a human-like manner at the speed of thousands of pages per second.

How Marketers Can Use Big Data for Digital Marketing Success

DataFloq

For that, companies need to focus on big data. . Marketing without data is like driving with your eyes closed.“ - Dan Zarrella. Today, big data plays an important role when it comes to marketing decisions. Big Data

3 Concepts Defining the Future of Work: Data, Decentralisation and Automation

DataFloq

Those enterprises that are aware of the upcoming changes can best prepare and achieve competitive advantage in a data-driven society. The Future of Work is Data-driven. Big data has been around for some time now.

5 fundamental questions for your data journey

IBM Big Data Hub

To accelerate its journey to AI, a data-driven organization needs a trusted data foundation that empowers information stakeholders.

Rearchitecting Unstructured Storage

Nutanix

Unstructured data is typically comprised of data that is not easily searchable, including such formats as audio, video, and social media postings. It has an internal structure but is not structured via pre-defined data models and may be textual or non-textual, and human- or machine-generated. It is typically stored on file and object storage

Semantic Search for Smart Data Discovery in the Pharma Industry

Ontotext

Today, with the invention of the World Wide Web and the subsequent digitalization, we live in the Fourth Industrial Revolution where data, data exchange and cognitive computing are transforming all industries and services, including Life Sciences and Pharma.

Rearchitecting Unstructured Storage

Nutanix

Unstructured data is typically comprised of data that is not easily searchable, including such formats as audio, video, and social media postings. It has an internal structure but is not structured via pre-defined data models and may be textual or non-textual, and human- or machine-generated. It is typically stored on file and object storage

5 Key Updates from Day 1 of Oracle OpenWorld 2019

Perficient Data & Analytics

Significant increase in data centers by end of 2020. New Exadata machine with persistent memory built in (yes that means an entire database can reside permanently in memory – which means extremely low latency for data access). Data & Analytics News Oracle

Text Analytics – Understanding the Voice of Consumers

BizAcuity

Text analytics helps to draw the insights from the unstructured data. . Text Analytics – is a process of turning unstructured text – available in the form of tweets, comments, reviews, etc.

New Software Development Initiatives Lead To Second Stage Of Big Data

Smart Data Collective

The big data market is expected to be worth $189 billion by the end of this year. A number of factors are driving growth in big data. Demand for big data is part of the reason for the growth, but the fact that big data technology is evolving is another. Unstructured.

Data Lakes on Cloud & it’s Usage in Healthcare

BizAcuity

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. Deploying Data Lakes in the cloud.

Semantic Search for Smart Data Discovery in the Pharma Industry

Ontotext

Today, with the invention of the World Wide Web and the subsequent digitalization, we live in the Fourth Industrial Revolution where data, data exchange and cognitive computing are transforming all industries and services, including Life Sciences and Pharma. It is even more complicated because often the proprietary information generated in-house needs to be complemented with a vast amount of valuable open data.

Smart Analysis of Pharma Research Literature Makes Novel Therapy Identification Easier

Ontotext

But while the exponential growth of information is a welcome development for medical research, analyzing these vast amounts of data is time-consuming and, often, inefficient. The Solution to the Data Challenge.

Measure Twice, Cut Once: How the Right Data Modeling Tool Drives Business Value

erwin

The need for an effective data modeling tool is more significant than ever. For decades, data modeling has provided the optimal way to design and deploy new relational databases with high-quality data sources and support application development.

Key Differences between a Traditional Data Warehouse and Big Data

Perficient Data & Analytics

Traditional data warehouse solutions were originally developed out of necessity. The data captured from these traditional data sources is stored in relational databases comprised of tables with rows and columns and is known as structured data. So how do you make the data gathered more useful? This process begins with data consolidation tools like Informatica or Oracle Data Integrator. What is Big Data? Multi-Structured Data.

Cloudera Data Warehouse – A Partner Perspective

Cloudera

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. Director of Products and Solutions, Arcadia Data.

Handling real-time data operations in the enterprise

O'Reilly on Data

Getting DataOps right is crucial to your late-stage big data projects. Data science is the sexy thing companies want. The data engineering and operations teams don't get much love. Let's call these operational teams that focus on big data: DataOps teams.

In Oil and Gas, it’s Time to Imagine How to Integrate and Interpret Data to Improve Wells Mastering

Tamr

What if the industry had new technologies and approaches to integrate and interpret data to drive faster, smarter, more accurate, and less risky decisions? . Wells mastering is the process of capturing and analyzing the data that’s captured about a well.

Data-Driven Digital Marketing Carves Competitive Edge For SMEs

Smart Data Collective

Big data is playing a vital role in the evolution of small business. A compilation of research from the G2 Learning Hub Shows the number of businesses relying on big data is rising. Big Data Helps Small Businesses Excel with Digital Marketing.

Postgres vs. MongoDB for Storing JSON Data — Which Should You Choose?

Sisense

Constraints and Limitations Native JSON Data Stores Performance Use Cases and Factors. When you get down to it, this is precisely the debate that rages among data scientists when it comes to PostgreSQL vs. MongoDB, and the right kind of storage for JSON data. What is JSON?

Smart Analysis of Pharma Research Literature Makes Novel Therapy Identification Easier

Ontotext

But while the exponential growth of information is a welcome development for medical research, analyzing these vast amounts of data is time-consuming and, often, inefficient. The Solution to the Data Challenge.

3 Trends from Gartner Data & Analytics Summit

Tamr

In March, I attended the Gartner Data & Analytics Summit in Orlando, Florida. It was an energetic and interesting event with sessions that focused on topics such as data science and machine learning, building a data-centric architecture, and innovation in data and analytics. Unstructured Data Continues to Grow. Doing so, of course, requires a unified view of the customer using data collected from several points of contact.

Top 10 Analytics Trends for 2019

Timo Elliott

We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s. These data-driven, self-learning business processes improve automatically over time and as people use them.

Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. But being an inquisitive Sherlock Holmes of data is no easy task. What Is A Data Science Tool?

Improving Big Data Analytics To Address Cybersecurity Challenges

Smart Data Collective

Advances in mass storage and mobile computing brought about the phenomenon we now know as “big data.” That is how “big” the need for big data analytics came to be. More specifically, big data analytics offers users the ability to generate relevant insights from heaps of data.