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

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

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.

What is Big Data Analytics?

Mixpanel on Data

Companies use big data analytics to uncover new and exciting insights in large and varied datasets. It helps them forecast market trends, identify hidden correlations between data flows, and understand their customers’ preferences in fine detail. Big data also moves fast.

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.

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.

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.

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

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.

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.

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.

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.

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?

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.

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.

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.

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.

OLAP and Hadoop: The 4 Differences You Should Know

Perficient Data & Analytics

OLAP is a technology to perform multi-dimensional analytics like reporting and data mining. Hadoop is a technology to perform massive computation on large data. For transactions and data mining use OLAP. But, for analytics and data discovery use Hadoop. 2 Data Size.

OLAP 52

Turning petabytes of pharmaceutical data into actionable insights

Cloudera

That’s the equivalent of 1 petabyte ( ComputerWeekly ) – the amount of unstructured data available within our large pharmaceutical client’s business. Then imagine the insights that are locked in that massive amount of data. Authors: Mai N.

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.

Acquisitions on the Horizon in BI and Data Analytics Industry?

Sisense

2019 can best be described as an era of modern cloud data analytics. Convergence in an industry like data analytics can take many forms. It’s an exciting time to be in the data analytics industry and there’s a dynamic year of convergence and consolidation still ahead for us. Two orthogonal approaches to data analytics have developed in this decade of BI: 1. This is typically done on top of a high-performance database and, these days, on top of a cloud data warehouse.

5 Digital Transformation Interests for IT Service Providers

Perficient Data & Analytics

The biggest problem these organizations face with their AI is either that the data is not available for AI or there is not enough sample set population for the AI to provide an unbiased approach. PR News estimated the big data market in 2023 to grow at a compound annual growth rate of 29.7%

AML: Past, Present and Future – Part III

Cloudera

The system must: Ingest, process, analyze, store, and serve all types of AML data, be it structured (database tables), unstructured (contracts, e-mails, etc.), Handle increases in data volume gracefully. Provide audit and data lineage information to facilitate regulatory reviews.

An Introduction To Data Dashboards: Meaning, Definition & Industry Examples

datapine

“It is a capital mistake to theorize before one has data.”– Data is all around us. Data has changed our lives in many ways, helping to improve the processes, initiatives, and innovations of organizations across sectors through the power of insight. What Is A Data Dashboard?

Test principles – Data Warehouse vs Data Lake vs Data Vault

Perficient Data & Analytics

Understand Data Warehouse, Data Lake and Data Vault and their specific test principles. This blog tries to throw light on the terminologies data warehouse, data lake and data vault. Let us begin with data warehouse. What is Data Warehouse?

Mastering Data Variety

Tamr

Data variety — the middle child of the three Vs of Big Data — is in big trouble. . It’s in the critical path of enterprise data becoming an asset. Meanwhile, most enterprises have unconsciously built up extreme data variety over the last 50+ years.

Is AI Enhancing or Disrupting FP&A as We Know It?

Jedox

As organizations strive to implement an analytics culture for data-driven decision making, AI can be an important component in that process. AI can enable the FP&A function to flourish and thrive by supporting the development and improvement in our people, data, processes, technology and performance indicators. These new tools will support ad-hoc reporting that can leverage unstructured data.

Why AI is the Driving Force Behind Financial Sector’s Intelligent Makeover

bridgei2i

Financial sector uses crucial customer data that needs to be handled carefully and without error. AI enables thorough research and understanding of concepts and continued learning of vast volumes of data.

Sales 77

Motorbikes, Movies, and Margarita Pizza: How AI and IoT are Revolutionizing Business

bridgei2i

Financial sector uses crucial customer data that needs to be handled carefully and without error. AI enables thorough research and understanding of concepts and continued learning of vast volumes of data.

IoT 52

Why AI is the Driving Force Behind Financial Sector’s Intelligent Makeover

bridgei2i

Financial sector uses crucial customer data that needs to be handled carefully and without error. AI enables thorough research and understanding of concepts and continued learning of vast volumes of data.

Sales 52

Modernize Using The BI & Analytics Magic Quadrant

Rita Sallam

It is defined by a self-contained architecture that enables nontechnical users to autonomously execute full-spectrum analytic workflows from data access, ingestion and preparation to interactive analysis, and the collaborative sharing of insights.