Data modelling vs. data architecture: What's the difference? by/via David Loshin

Data modellers and data architects have distinctly different roles, but they work in a complementary fashion to help enterprises unlock and capitalize on data's business value.

It's a pretty important job definition difference and a key one for people to understand.

3 tips on how to stop misusing or under-utilising corporate data by Alex Toews via @Infomgmt

Few organizations have assessed how their data can be put to work in the most productive way. This leaves them vulnerable to inefficiencies and can prevent important information from making its way 'to the top.'

A data model is a great place to start as you can begin to understand how the data relates to each other. The data dictionary is also useful as you can see which fields are repeated which is crucial if you want to understand how you can join data together from different sources. Just pay attention to formats and if any conversion needs to be done.

GDPR compliance the perfect opportunity to modernise data architecture by Amandeep Khurana via @infomgmt

Compliance with the data privacy and security mandate enables organisations to become more agile in their product and service development and rollouts, and more efficient and effective in their ability to respond to market trends and competitive threats.

Yes this is exactly right - everything has to turn onto it's head and be data centric not application centric. I think we need to concentrate on:

WHERE is the data created
WHERE is it also stored (so where is it interfaced to)
HOW it is updated
WHAT changes when it is updated
HOW do you delete the data in ALL systems?

I would suggest you do something like a data flow diagram so you can document all of this for every piece of data.

Who Needs A Data Model Anyway? by @BarryDevlin via @TDWI

Will AI eliminate the need for data models?

I come from a data modelling background so I'm biased but I still think there is a home for a data model. An Enterprise Data Model would be very useful as a tool to help non-technical people understand the business and how the data within it relates.

As NoSQL thrives, so does data modelling by Pascal Desmarets via @infomgmt

But a new approach is needed to support agile development.

Here are a couple of useful articles on Agile Data Modelling:

Agile/Evolutionary Data Modelling: From Domain Modelling to Physical Modelling by @scottwambler

and

Fundamentals of Data Modelling in Agile Environments by Jelani Harper

The 3 most important data metrics for retaining customers by Matthew Tharp via @infomgmt

In an era where every customer is valuable, it’s important to use information to more deeply understand the most profitable and high-growth segments and tailor the business to them.

Some great suggestions on metrics as keeping customers is definitely cheaper than getting new ones.

Developing a successful data governance strategy by Federico Castanedo via @OReillyMedia

Multi-model database architectures provide a flexible data governance platform.

Great article by Federico that is worth reading. There is a free e-book you can download too.

Mastering data architecture to enable digital transformation by Joshua Satten and Nicolas Papadakos via @infomgmt

The information model is the gas powering the engine, enabling organisations to more effectively communicate and reach their specific goals.

Some good points. I would add to it that you need to try and balance the needs of the business, the availability of data and as mentioned in the article you need to focus of granularity in order to get that right.  Business knowledge is key.  Also be aware that documentation can sometimes we scarce so be prepared to have to generate your own for some older data/systems.

6 data modeling best practices for better business intelligence by Kayla Matthews via @infomgmt

Although specific circumstances vary with each attempt, here are six tips to follow that should improve outcomes and save time.

I definitely agree with some of these observations.  Time, Status and history of values are all very useful at times. However be guided by the requirement - just be sensible in your design so you could extend it easily - you need to keep the future in your mind so check the roadmap of projects coming up in case they impact even slightly.

You will find this link useful - slowly changing dimensions

Why Big Data Enhances the Need for Enterprise Information Management by @s11ravindra via @datanami

Many EIM (enterprise information management) or data management programs do not live up to their potential, and the arrival of big data makes the need for enterprise information and data management even more significant.

The article makes a number of great points and I have to agree with him. It all sounds great and sounds like an ideal set of systems to work on. I think this could give you the start of a blueprint of what needs to be in place for success.

Data Modelling and E-R Diagrams by Nagesh Kumar G via @DataScienceCtrl

We can subdivide the process of designing a database into three separate phases: Data Analysis, System Design, and Technical Design.

I would also draw you attention to normalisation.

And slowly changing dimensions.

The Rise of the Data Engineer by @mistercrunch via @freeCodeCamp

This great article shows how the transition from business intelligence engineer to data engineer. This is a great article and makes so much sense.  Definitely a must read article.

On a personal note I feel I am probably closer to a data engineer then to a data scientist.

SLIDESHOW: Data Pay Days: The 12 Top Paying Noncertified Data Skills via @infomgmt

Data Pay Days: The 12 Top Paying Noncertified Data Skills by David Wedon via +Information Management - There seems to be no end in sight when it comes to high demand for data professionals. But just how well an individual can cash in on that trend depends on their job experience, location, and acquired skills. This week we look at how all those factors impact the paycheck. Today we review the pay premiums being paid in 2016 for the top noncertified data skills.

The 3 A’s of Enterprise Integration via @Data_Informed

The 3 A’s of Enterprise Integration by @rdharn1 via @Data_Informed - Modern organizations require real-time insight based on structured and unstructured data from an ever-growing number and variety of sources. Ravi Dharnikota of SnapLogic offers tips for identifying the right data integration platform for your organization’s needs.

Very useful way of thinking and should mean you can handle whatever comes next as you have covered it already as a possibility.

VIDEO: Data modelling constructs and terminology via @radar

Data modelling constructs and terminology by David Blaha via @radar - Identification of data sources is the first step in warehouse development. In this free video training segment, Michael Blaha provides a framework by reviewing data modelling constructs and terminology, including dependent and independent entity types. Using IE (information engineering) notation and the ERwin tool, Michael walks you through a sample operational data model.

Quite basic but useful if you need an introduction

Resolving 3 Crucial Bottlenecks of Data Processing in BI Software via @infomgmt

Resolving 3 Crucial Bottlenecks of Data Processing in BI Software by Eldad Farkash via +Information Management - While modern tools provide great performance for smaller and simpler datasets, they tend to buckle down under the pressure of dealing with big data, disparate data sources, or many concurrent users.

A great feature article with some real solutions to common physical problems to using BI.

The Emerging Data Design: Bitemporal Data via @infomgmt

The Emerging Data Design: Bitemporal Data by Mike Lapenna via +Information Management - Many of us have been exposed to aspects of the bitemporal design by using time series data, temporal data, or historical data.

This is a part 1.  We should all be doing this in our designs, and it makes like easier in the long run to be able to show changes over time.

WEBINAR: Empowering the Citizen Data Scientist with Self-Service Advanced Analytics - 19 November 2015

Empowering the Citizen Data Scientist with Self-Service Advanced Analytics Date: Thursday, November 19^th  Time: 11 a.m. ET (60 min)

The tsunami of valuable data has hampered the ability of the few highly skilled technologists to take advantage of it. To bridge the gap, more and more companies are providing advanced analytics tools to its super users – a group Gartner calls “citizen data scientists.” In this live, one-hour webinar, you’ll learn how democratizing data can help:

• quickly place massive data sets into a business context and provide critical insight
• more easily tap into predictive modeling and other sophisticated analyses once reserved for data technologists
• explore new methods of analyzing data that can lead to cutting-edge decision making.

Presenters:Dan Donovan, Lead Technology Evangelist, Lavastorm 

Dan Donovan is the Lead Technology Evangelist at Lavastorm and served in several strategic roles including Head of Partner Development and Director of Customer Solutions. Earlier in his career he held various technical roles at Telution, IKON and FreeDrive. With over 15 years of software experience, Mr. Donovan has a deep understanding of the evolving big data market and the challenges that enterprises face with blending complex, large-volume data sets, often from disparate sources, in order to produce accurate data insights for the business. He earned a BS in chemistry and computer science from the University of Illinois.

Register here

WEBINAR: Three Things You Need to Know About Document Data Modeling in NoSQL - 12 November 2015

Three Things You Need to Know About Document Data Modeling in NoSQL

DATE: Thursday, November 12, 2015

TIME: 1PM ET

We’re all familiar with modeling data the relational way. When we move to a document database we need to think about things a little differently. In this webinar, we’ll show you how to best plan, model and maintain your data using a NoSQL document database.

Join Matthew Revell, Dir. Developer Advocacy at Couchbase, as he takes you through some brand new NoSQL capabilities that will allow you more flexibility when modeling your data including:

• Basic hygiene for modelling sustainable JSON documents
• Creating manual secondary indexes
• Automating secondary indexing with views
• Modelling documents for the best level of query-ability

FEATURED SPEAKER:

Matthew Revell

Dir. Developer Advocacy, Couchbase

Register here

WEBINAR: Facing the Future of Data Modeling 10 November 2015

Great Scott! Dealing with New Datatypes

Tuesday, November 10, 2015
11:00am Pacific / 2:00pm Eastern

Data modeling is going back to the future! No, it doesn't include a hoverboard (yet), but it does include some new datatypes that capture temporal and spatial information. In the past, datatypes were used to classify various types of data, whether integers, characters, or alphanumeric strings. With the technologies introduced in recent years, these basic datatypes can’t address everything – data modelers now need more specialized datatypes for specific needs and new formats.

Multiple database platforms have introduced new datatypes that can make it easier to support more advanced data concepts in physical data models. If you do not know about what new things are happening in the physical data modeling world, or what to do with them, Karen Lopez will discuss using a variety of new datatypes including:

• Temporal, such as period, with keywords
• Spatial, including geospatial
• Others, incorporating JSON/BSON/UBJSON usage

About Karen Lopez Karen López is Senior Project Manager and Architect at InfoAdvisors. She has more than twenty years of experience in helping organizations implement large, multi-project programs. She is a Microsoft MVP, SQL Server, and a Dun and Bradstreet MVP. InfoAdvisors is a Toronto-based data management consulting firm. We specialize in the practical application of data management. Our philosophy is based on assessing the cost, benefit, and risk of any technique to meet the specific needs of our client organizations.

Register here