Understanding Structured and Unstructured Data

Sisense

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive.

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

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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

Proptech is the Next Big Industry to be Disrupted by Big Data

DataFloq

Through the capacity to make more accurate appraisals on a massive scale, to more personalised real estate marketing, better risk mitigation and quicker processing times for applications, big data is in the process of completely upending the real estate industry - in a good way.

5 Ways AI and Big Data Are Changing the Customer Experience

DataFloq

Here’s how you can use AI-driven technologies to leverage the power of data and improve customer experience: 1. Support Real-Time Data-Drive Decision-Making. purchase history, demographic data, preferences) with real-time browsing behaviors. Big Data Artificial Intelligence

The Incredibly Important Role Of Big Data In Academia

Smart Data Collective

According to a 2015 whitepaper published in Science Direct , big data is one of the most disruptive technologies influencing the field of academia. Now it has become so popular that you can even get data structure assignment help from professionals. Big Data Internal Impact.

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. InfoSec specialists, in particular, find big data analytics very helpful in analyzing online threats.

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.

How To Transform The Customer Journey With AI And Big Data

Smart Data Collective

This is slowly changing with the emergence of AI and big data to solve these challenges. In this post, we’re going to take a closer look at AI and big data and how they can transform the customer journey. What is Big Data?

Big Data Sets New Standards In Stream Processing For Emerging Markets

Smart Data Collective

Data, for instance, has to be processed fast so that the companies can keep up to the changing business and market conditions in real time. This is where real-time stream processing enters the picture, and it may probably change everything you know about big data.

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.

Five Modern Data Architecture Trends

David Menninger's Analyst Perspectives

I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data.

Who Needs Big Data Analytics Software?

Jet Global

Of all the transformative effects the internet has had on the world of business, none is more dramatic than the proliferation of data it has enabled. According to DOMO’s annual report on data generation , over 2.5 Big Business Needs Big Data.

Governance in Healthcare: Big Data is Table Stakes

Perficient Data & Analytics

Big data itself does not alter the approach to governance nor its framework. And big data isn’t just about data – it’s also concerned with managing and governing vast amounts of content of varying types such as video, images, voice, etc.

Who Needs Big Data Analytics Software?

Jet Global

Of all the transformative effects the internet has had on the world of business, none is more dramatic than the proliferation of data it has enabled. According to DOMO’s annual report on data generation , over 2.5 Big Business Needs Big Data.

Approaches to Embrace Big Data

Perficient Data & Analytics

Not every organization starts its big data journey from the same place. However, in order to drive efficiencies, support expected future growth and to continue its evolution to a data-driven company, most organizations are reviewing their current suite of software solutions, platforms and documenting processes and areas of improvement along with devising and executing a strategy to deploy modern business intelligence capabilities. Baby Steps from EDW to Big Data.

A Big Data Imperative: Driving Big Action

Occam's Razor

Is there anything in the analytics space that is so full of promise and hype and sexiness and possible awesomeness than "big data?" So what is big data really? As I interpret it, big data is the collection of massive databases of structured and unstructured data.

Big Data, Big Benefits: What Leaders Say

Sisense

Data’s more influential than ever, but just how much data is there? In The Wide World of Data , we dig into astonishing facts and trends about the size and growth of the datasphere, how data is being used, and how it truly makes up the entire world around us.

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.

Technology Driven Insurance Data Analytics

DataFloq

The nature of the Insurance industry being data-centric, insurers abide by the policy of keeping data as a treasure for their respective growth. Big Data Technical

Skills and Tools Every Data Engineer Needs to Tackle Big Data

Sisense

As a company that touts the benefits of a full end-to-end BI solution, we certainly know the value of a data engineer. The data engineer’s job is to extract, clean, and normalize data, clearing the path for data scientists to explore that data and build models.

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

6 Spectacular Reasons You Must Master the Data Sciences in 2020

Smart Data Collective

The global demand for big data is surging. Is the Booming Big Data Field Right for You? Everyone has heard about Data Science in 2020. First, you should learn how Data Science is relevant to yo u, whether you will like, and if there are opportunities for you.

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.

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.

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.

Deep Learning Would Be Crucial Under Sanders’s Medicare for All System

Smart Data Collective

He should elaborate more on the benefits of big data and deep learning. A lot of big data experts argue that deep learning is key to controlling costs. Health IT Analytics wrote an article on the cost benefits of using big data in healthcare.

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.

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.

10 Invisible Secrets of Data Scientists

DataFloq

quintillion bytes of data, it is so much that 90% of the data accretion on the internet has been built since 2016. All these pieces of information consist of disorganized or sloppy data which offers a great challenge in terms of analysis either by humans or any automated machines.

Common Ingestion Framework

Perficient Data & Analytics

Big Data is the way to move forward for all enterprises today. May it be healthcare, retail, finance or manufacturing, everyone is at different stages in their journey to create their industry-grade, enterprise-ready Data Lake repository.

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.

Taking out the threat from the inside

Cloudera

This could be in the form of reputational damage or unfavorable regulatory consequences in case of compromised customer data, for example. Moreover, this approach struggles to deal with the large volume and variety of data that must be analyzed and often correlated.

Cross-Functional Trade Surveillance

Cloudera

This post describes how native visual analytics on a Cloudera Enterprise Data Hub is the keystone that supports a holistic trade surveillance program. Market data: Coordinated trading among multiple parties. However, in this case, that output is ingested into a data lake.

Are you valuing Data as an asset on your Balance Sheet?

Perficient Data & Analytics

Thriving companies, innovators, value their data as an asset. They use big data solutions as a competitive advantage to increase revenue, reduce cost, and improve cash flow. Data is woven into the fabric of every organization. Any business leader looking to maximize their data needs to ask themselves: Does your organization have a comprehensive data strategy? Does that strategy address both structured and unstructured data?

Time Series Analytics – Making Manufacturing Use Cases Come to Life

Cloudera

Time series data and real-time data acquisition is growing at a 50% faster rate than static, latent, or historical data. Time series data and real-time data acquisition dominate industrial use cases, as it is ubiquitous with the manufacturing process.

Operational Database in CDP

Cloudera

Cloudera’s operational database (OpDB) in CDP delivers a real-time, always available, scalable OpDB that serves traditional structured data alongside new unstructured data within a unified Operational and Warehousing platform.

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.

Customers and Banks Priorities Collide as AI Jolts Financial Industry

Smart Data Collective

In a previous article I shared some of the challenges, benefits and trends of Big Data in the telecommunications industry. Big Data’s promise of value in the financial services industry is particularly differentiating. quintillion bytes of data are created every day.

Understanding Social And Collaborative Business Intelligence

datapine

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Social BI indicates the process of gathering, analyzing, publishing, and sharing data, reports, and information.

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.

Top 10 Analytics And Business Intelligence Buzzwords For 2020

datapine

Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. The accuracy of the predictions depends on the data used to create the model. This data analytics buzzword is somehow a déjà-vu. Data Fabric.