The peterjamesthomas.com Data Strategy Hub

Peter James Thomas

Today we launch a new on-line resource, The Data Strategy Hub. This presents some of the most popular Data Strategy articles on this site and will expand in coming weeks to also include links to articles and other resources pertaining to Data Strategy from around the Internet.

How Data Strategy and Machine Learning Intersect

TDAN

Are you worried about the security of your valuable data? Well, with the massive growth of business data in terms of complexity, volume and size, it is basic for worldwide associations to build up a strong data technique to address the main business needs.

The Insights Beat: Save Your Data Strategy From A Nosedive

Srividya Sridharan

This month’s Insights Beat focuses on the latest research in our insights-driven playbook; showcases multiple data, analytics, and machine-learning vendor evaluations; and shines a light on B2B analytics techniques. Is Your Data Strategy Lacking?

Data Strategy at Strata Data Conf New York

Perficient Data & Analytics

It’s no secret that data is a massive asset when it comes to making better business decisions. But gaining the valuable insights required to make those decisions requires quality data that you can trust. And to accomplish this you need a data strategy.

Data Strategy & Insights 2019: Reimagine To Reinvent

Srividya Sridharan

Discover the themes and topics we'll be tackling at this year's Data Strategy & Insights Forum. advanced analytics analytics applications artificial intelligence (AI) customer analytics data insights data management data quality & data governance predictive analytics privacy web analytics promoted

Supercharge your data strategy

Data Insight

By Carmen Vicelich, Data Insight CEO We’re now living in the age of the customer. They show us they know us and use data to add value to their customers’ lives. Data Audit: What is the quality of your data? Knowing where you are today : Where are you on your data journey?

6 Tips for Building a Training Data Strategy for Machine Learning

KDnuggets

Without a well-defined approach for collecting and structuring training data, launching an AI initiative becomes an uphill battle. These six recommendations will help you craft a successful strategy. 2019 Sep Opinions Advice Machine Learning Training Data

Data Strategy Framework: Handle with CARE

Perficient Data & Analytics

Although information is still not recognized as a line item in a corporate balance sheet (data as an asset), it is still a strategic asset that can drive business value. Therefore, it’s important to have data strategy framework in place. Data Strategy Components.

Unleash the power of data with a modern data strategy

IBM Big Data Hub

In my last blog , I stressed the need for a modern data architecture (MDA) to underpin the next generation of the cognitive enterprise , fully harness data using the latest technologies, and sustain a

Strategy is Unleashing the Potential of Enterprise Data

Corinium

Enterprises across the globe are waking up to the fact that data is an asset that requires its own strategy. Data StrategyThose that treat it as such are now seeing substantial returns on their investments.

Closer Than You Think: Data Strategies Across Your Company

Sisense

It doesn’t matter what you think your company does, it’s going to have to turn into a data company soon, if it hasn’t started already, in addition to continuing to provide your core product or service. This may sound daunting, but it’s a good challenge to have and one that will ultimately improve your offering, delight your customers, increase stickiness and adoption , and keep you competitive in a changing data landscape. . Data Strategies for the Uninitiated.

4 things to consider when setting your fast data strategy

IBM Big Data Hub

In the study, the definition of fast data starts with the technical characteristics mentioned in our last article, but there’s more to that definition

Voice of the Client: Is AI your priority? Start with a data strategy

IBM Big Data Hub

Intel's Melvin Greer, Senior Principal Engineer and Chief Data Scientist, Americas writes about the data strategy necessary to execute the promises of AI and touts their collaboration with IBM on Cloud Pak for Data.

Enterprise Data Strategy: The Upside of Scarce Funding

Teradata

In a cost-cutting culture, directly linking data projects to top business initiatives is a good way to keep them from getting clipped. Learn more

Is your data strategy being hurt by these 3 cloud myths?

IBM Big Data Hub

Aberdeen reports that nearly 80% of businesses in their study are now using public cloud. But that still leaves over 20% of businesses that are not availing themselves of the benefits of public cloud

Don’t wait to set your data strategy as Netezza goes end of support

IBM Big Data Hub

Support for Netezza TwinFin and Striper models will end as early as June 2019, potentially leaving business-critical data in unsupported environments. Yet there’s no need for long-time Netezza customers to take those risks. The next stage in Netezza’s evolution has already arrived

Risk 59

Game-Changing Data Types for Your Business

TDAN

Data has a bad status across various business industries. Data doesn’t need any status as you don’t have the choice to overlook this aspect to maintain efficiency in your organization. It is always considered a boring, freaky, and time-consuming task. But who cares!

Introduction to Blockchain for DBAs

TDAN

Blockchain is a distributed, shared, permissioned ledger for recording transactions with consensus, provenance, immutability, and finality. It is the technology that drives virtual currencies like Bitcoin. But its potential spans many more industries and use cases than just virtual currencies.

Conceptual Modeling Requires Conceptual and Critical Thinking

TDAN

I am surprised to see a lot of people jumping straight into logical or even physical modeling and skipping conceptual modeling. Don’t they understand the value of conceptual modeling? Don’t they understand the difference between the various levels of modeling? Or do they have cognitive limitations?

Why non Data Scientists can lead Data Science teams

DataFloq

I recently discovered a LinkedIn debate over whether or not non-data scientists could lead data science teams. Andy Sutton is Head of Data & Personalisation for Endeavour Drinks in Australia. My Experience of Non-Data Scientists as Leaders. Big Data Strategy

Common Data Governance Challenges

TDAN

Organizations faced with the delivery of formal Data Governance or Information Governance programs recognize that there are several challenges they will face when getting started and as the program is operationalized.

Business Glossary and Metadata: Small Teams Data Governance

TDAN

In my last article I suggested that many organizations have approached Data Governance incorrectly using only centralize data governance teams and that approach is not working for many.

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.

Steps to an Effective Data Governance Structure

TDAN

The quality of data used in business is more important now than ever before. Accordingly, in order for organizations to deliver good business results, their data must be accurate, and the use of that data must be governed through policy and monitoring.

Data Engineering From A Data Scientist’s Perspective

DataFloq

We’ve had technical people focused on the ingestion and management of data for decades. But, only recently has data engineering become a critical, widespread role. It wasn’t long ago that the primary roles focused on enterprise data were largely involved with three primary areas.

Want To Contribute To An Upcoming Book?

DataFloq

The book is going to be called 97 Things About Ethics Everyone In Data Science Should Know. Our goal with the collection is to represent a wide range of voices and ideas from people who have a clear point of view on some aspect of the ethical issues surrounding the field of data science.

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.

AI and BI Are the New Digital Marketing Tools

TDAN

Consider that in 2019, one Internet minute is equivalent to 300,000 Instagram scrolls, 1 million Facebook logins, $1 million spent online, over 40 million messages sent, and almost 4 million Google searches.

Make an Impact: Data Governance’s Missing Piece

TDAN

It’s no secret that Data Governance is difficult to get right. The pattern usually goes something like this: 1) Executive sponsor gets excited about data, decides to do Data Governance (again) but get it right this time. Go-getters (aspiring Data Leaders) do a bunch […].

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.

Trends in Data Management and Analytics

TDAN

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years.

Cloud Computing to Make Noise in 2020

TDAN

Some industry experts say that just a couple of years ago, cloud computing was dismissed as the latest technology trend, which was good for generating a lot of noise.

Challenges Facing CIOs and IT Leaders

TDAN

There are a lot of big changes on the horizon in the world of technology. It seems like in the past few years things have already changed so dramatically that there’s no way we could be pushed any further from our comfort zone. In reality, that’s exactly what’s happening.

IT 70

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?

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.

Data Governance Roles and Responsibilities

TDAN

Roles and responsibilities are the backbone of a successful information or data governance program.

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.

Cloud Computing for Startups

TDAN

In the wake of online security threats, more and more companies are turning to cloud computing in search of better protection. According to Forbes, 83% of enterprise workloads will be in the cloud by 2020.

Data Management 20/20: Connecting the Data

TDAN

Data collection is getting more dispersed and voluminous every day. Enterprises create and collect information from a variety of data sources which may include websites, mobile devices, customers, vendors, and other numerous sources.

Tips for Gathering Business Intelligence

TDAN

Gathering business intelligence is a process that starts from within. Collating internal intelligence is of vital importance before searching the market. Oftentimes, the internal departments of your business will offer better suggestions and methods than any others you can find.