Cloud-Based Data Mapping Tools

TDAN

Cloud-based analytics is becoming a pivotal tool for today’s digital businesses. Out of its many advantages, the most significant one would be the ability to perform data mapping through cloud-based analytics.

Complicated vs Complex Problems

TDAN

Not that long ago our information needs seemed much simpler. If we wanted to make a phone call, we had a relatively simple device to help us do this, the humble rotary dial telephone. Similarly, for other technologies, they were built to do the job specified as simple as possible.

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Recognizing and Treating “Tableitis”

TDAN

Tableitis (tay-bul-eye’-tus) is a widespread condition suffered by professional data modelers, commonly called “TABLE THINK.” Most professional data modelers suffer from Tableitis… are you one of them?

Convert From Big Data to Smart Data

TDAN

Did you know that 90% of all data has been generated over the last 2 years? Big Data has been an important topic in the marketing scene for quite some time.

Differences Between ‘Available’ and ‘Accessible’

TDAN

A few months back, our company enjoyed a retreat a few hours north of the city. We bonded, brainstormed, and set visions and goals for the development of our company and our products. We also had bonfires with s’mores, and that’s more relevant than you might think.

Deep Learning Can Make a Difference

TDAN

Deep learning, as defined by MathWorks, is a system of artificial intelligence that is built around learning by example. Multiple industries have already understood the benefits that deep learning brings to their operational capabilities.

Start Thinking About DataOps

TDAN

Everyone’s talking about data. Data is the key to unlocking insight— the secret sauce that will help you get predictive, the fuel for business intelligence. It relies on data. The good news is that data has never […].

We Need Data Ethics Now

TDAN

What are the ethics of collecting, managing, and analyzing data? Is it going to come to regulations enforced by government and industry consortiums to make businesses think about data ethics with the goal of truly treating data ethically?

The Non-Invasive Data Governance Framework – The Details

TDAN

The third and final part of the Non-Invasive Data Governance Framework details the breakdown of components by level, providing considerations for what must be included at the intersections.

Understanding LIDAR Data and Applications

TDAN

LIDAR is a remote detecting innovation that utilizes the beat from a laser to gather data that measures and makes 3D models and maps of inaccessible articles and conditions.

Statistics Changing Marketing Strategies

TDAN

When it comes to marketing, business owners need to be fast in adjusting their strategies to fit the continuous advancement in technologies. Today, nearly everyone has a mobile phone or another smart mobile device with them at all times.

The Unfolding of the Data-Centric Paradigm – Part 1

TDAN

There is a movement to upend traditional thinking about information systems by putting data and meaning at the center of strategy, architecture, and system development sequencing. It is the most recent of a series of data-centric waves which, over several decades, have attempted to remedy the entrenched application-centric paradigm.

Database Administration Impacted by the Connected Economy

TDAN

Before the end of the decade, the number of connected objects is projected to expand greatly. According to several different analysts, the number of connected objects by 2020 could be as low as 26 billion or as high as 50 billion. But even the low end of that range is quite large.

Contrasting Power BI & MSBI

TDAN

MSBI & power BI are both well-known administrations in the Business Intelligence world now. It concentrates, transforms & loads data, can sort out and imagine multidimensional information, whereas, […]. In this way, here’s an article looking at both, MSBI versus Power BI, for your audience. Now, recall, MSBI can be a real commodity using ETL capacities.

IT 40

Lean Data Governance Strategies

TDAN

The goal of data governance is to ensure the quality, availability, integrity, security, and usability within an organization. The way that you go about this is up to you.

Make an Impact: Find the Angry People

TDAN

Whenever I’m invited to a new organization to help with data challenges, I look for them. I love angry people. This may sound strange but bear with me. Here is the reason why angry people are great: They have opinions, and they aren’t afraid of sharing them.

Considerations Before Adopting SaaS

TDAN

Software as a Service (SaaS) is becoming mainstream with a significant increase in both offerings and enterprise adoption. There are several advantages to SaaS – scalability, accessibility, and little to no Capex requirement, among others.

Big Data Hadoop vs. Traditional RDBMS

TDAN

Apache Hadoop is a comprehensive ecosystem which now features many open source components that can fundamentally change an enterprise’s approach to storing, processing, and analyzing data.

Principles for the Data-Centric Paradigm – Part 2

TDAN

There is a movement to upend traditional thinking about information systems by putting data and meaning at the center of strategy, architecture, and system development sequencing. Establishing a complete data-centric paradigm will require foundational principles which underscore the clear break with application-centric thinking, and which establish common ground on the unresolved issues inherited from the […].

Common Data Modeling Mistakes and Their Impact

TDAN

Although data modeling has been around for over 30 years, it ranks among the top areas from which database application problems arise. Today’s data modeling […].

DB Pros Need to Know Cloud Migration

TDAN

In 1961, Professor John McCarthy was the first to publicly suggest in a speech at the centennial celebration of the Massachusetts Institute of Technology that: “Computing may someday be organized as a public utility just as the telephone system is a public utility.

Agile vs. Lean Project Management

TDAN

The perfect project management style has yet to be discovered. For the curious project owner, exploring all the different project management methodologies is an enriching endeavor.

Birst automates the creation of data warehouses in Snowflake

Birst BI

Managing large-scale data warehouse systems has been known to be very administrative, costly, and lead to analytic silos. The good news is that Snowflake, the cloud data platform, lowers costs and administrative overhead.

DAMA International Community Corner: Announcements & New Chapters

TDAN

Welcome to DAMA Corner, a source of information for data management professionals here in TDAN.com, an industry-leading publication for people interested in learning about data administration, data management disciplines, and best practices. Each column provides an update on the professional organization DAMA International, and an opportunity to share your experience with other professionals that are passionate about data! […].

Artificial Intelligence Hope – Reinvent the ‘Broken’ Physician-Patient Relationship

TDAN

The physician job has become less and less focused on patients, and more and more preoccupied with the administrative and data-entry tasks that require attention and time. A study by the University of Wisconsin and the American Medical Association (AMA) found that primary care physicians spend almost 6 hours on EHR data entry during a […].

Tales & Tips from the Trenches: Distinguish Graph DBs from Other DBs

TDAN

Big Data Columns Big Data News, Articles, & Education Business Intelligence Columns Business Intelligence News, Articles, & Education Data Architecture Columns Data Columns Data Education Data Modeling Columns Data Modeling News, Articles, & Education Data Strategy Columns Data Strategy News, Articles, & Education Data Topics Metadata Management Columns Metadata Management News, Articles, & Education graph databases oneil RDBMS.

Flexible and secure Data-as-a-Service delivered today

Birst BI

How many duplicated, dirty data pipelines are running throughout your organization? To put it simply, by setting up DaaS, Birst offers a better way to democratize data without sacrificing security, governance, and control. DaaS is a core component of modern data architecture.

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 this chat, let’s avoid the concern of price and also assume the business needs have been thought through.

OLAP 56

A Simple Data Capability Framework

Peter James Thomas

As part of my consulting business , I end up thinking about Data Capability Frameworks quite a bit. Sometimes this is when I am assessing current Data Capabilities, sometimes it is when I am thinking about how to transition to future Data Capabilities. Data Strategy.

Convergent Evolution

Peter James Thomas

No this article has not escaped from my Maths & Science section , it is actually about data matters. That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Of course some architectures featured both paradigms as well.

The latest edition of The Data & Analytics Dictionary is now out

Peter James Thomas

After a hiatus of a few months, the latest version of the peterjamesthomas.com Data and Analytics Dictionary is now available. Business Glossary (contributor: Tenny Thomas Soman ). Data Architecture – Definition (2). Data Catalogue. Data Community.

Join Us at MicroStrategy World 2020

Perficient Data & Analytics

Perficient is proud to be a Silver sponsor of the event this year and our experts look forward to meeting you in the expo hall where we’ll share how we can help deliver data-driven insights that empower you to make more-informed business decisions.

How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. Managing metadata should not be a sub-goal of data governance. Quite simply, metadata is data about data.

How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. Managing metadata should not be a sub-goal of data governance. Quite simply, metadata is data about data.

Learn Microsoft BI Stack

Ms SQL Girl

This is a much belated follow up to my very first blog post Open Your Mind To Business Intelligence from 4 years ago. Chapter 2 Designing an Eff ective Business Intelligence Architecture. Chapter 3 Selecting the Data Architecture that Fits Your Organization.

Key Differences between a Traditional Data Warehouse and Big Data

Perficient Data & Analytics

Traditional data warehouse solutions were originally developed out of necessity. In order to run the business, every company uses enterprise resource planning (ERP) and CRM applications to manage back-office functions like finance, accounts payable, accounts receivable, general ledger, and supply chain, as well as front-office functions like sales, service, and call center. So how do you make the data gathered more useful? That’s where business intelligence comes into play.

Snowflake: A New Blueprint for the Modern Data Warehouse

Sirius Computer Solutions

Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. Data migration and integration.

5 Ways Data Modeling Is Critical to Data Governance

erwin

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan.

Modernizing and optimizing enterprise reporting [Infographic]

BI-Survey

Many reporting systems today are failing to provide adequate support to users while much of the content created is unused or lacks relevance to the most important business questions. Only a minority of companies say they have a modern reporting landscape and regularly base decisions on data.

Okay, You Got a Knowledge Graph Built with Semantic Technology… And Now What?

Ontotext

With several examples, you will see how knowledge management can be made smarter using the potential of semantic technology to fuse data, analyze relationships, detect patterns and infer new facts from enriched datasets. .

Why Your BI and Analytics Platform Should be Cloud-Agnostic

Sisense

With the introduction of VMware in the 1990s, developers embraced the ability to run their applications on virtual machines that could then run on any physical machine architecture. What does it mean for your data? You Should be Able to Store Your Data In Any Cloud.

Three Trends for Modernizing Analytics and Data Warehousing in 2019

Cloudera

Data analytics priorities have shifted this year. Growth factors and business priority are ever changing. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Big Data Technologies and Architectures.

Okay, You Got a Knowledge Graph Built with Semantic Technology… And Now What?

Ontotext

Whether you refer to the use of semantic technology as Linked Data technology or smart data management technology, these concepts boil down to connectivity. Connectivity in the sense of connecting data from different sources and assigning these data additional machine-readable meaning.