Smart Data Collective

MARCH 18, 2020

Big data is changing the direction of small and medium sized businesses. They can use big data for many purposes. However, the value of their big data strategies will vary considerably. Using big data to get a better understanding of your customers is important.

Data mining 90

Data mining Sales Data Strategy ROI 90

DataFloq

APRIL 30, 2019

Data mining and clustering are closely interlinked. They help in discovering patterns in data. Clustering is one of the various methods of data mining. What is clustering in data mining? Generally, the mining of data ends up at spotting the pattern.

Data mining 225

Data mining Statistics Machine Learning IT 225

Data Science 101

OCTOBER 31, 2019

Today we are generating data more than ever before. Over the last two years, 90 percent of the data in the world was generated. This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Machine learning provides the technical basis for data mining.

Data mining 53

Data mining KDD Forecasting Knowledge Discovery 53

DataFloq

OCTOBER 23, 2019

Data mining, a process that involves identifying patterns and anomalies in large data sets, is widespread among many of today’s companies. Experts predict the big data market will reach $103 billion in revenue by 2027, far exceeding 2019's predicted $49 billion. Big Data

Data mining 169

Data mining Reporting Modeling Marketing 169

DataFloq

MARCH 28, 2019

Companies receive information in the form of digital data or content, more commonly in the shape of performance and user metrics. The entire operation that involves collecting data, processing it and then putting it to use is called business intelligence. Big Data

Data mining 257

Data mining Data Warehouse Metrics Business Intelligence 257

Jet Global

JUNE 5, 2019

The path to doing so begins with the quality and volume of data they are able to collect. But data alone is not the answer—without a means to interact with the data and extract meaningful insight, it’s essentially useless. Let’s introduce the concept of data mining.

Data mining 83

Data mining Business Intelligence OLAP Key Performance Indicator 83

Analytics Vidhya

JUNE 7, 2020

Overview SQL is a mandatory language every analyst and data science professional should know Learn about the basics of SQL here, including how to. Beginner Data Mining Database Programming Python SQL Structured Data database RDBMs sql analytics sql data sql data science sql for beginners sql sqlite SQLiteThe post SQL for Beginners and Analysts – Get Started with SQL using Python appeared first on Analytics Vidhya.

Data mining 208

Data mining Structured Data Data Science Analytics 208

Analytics Vidhya

MAY 31, 2020

Overview Feature engineering is a key aspect in acing data science hackathons Learn how to perform feature engineering here as we walk through a. The post Want to Ace Data Science Hackathons? Beginner Data Engineering Data Mining Machine Learning Python datahack feature engineering feature importance pythonThis Feature Engineering Guide is for you appeared first on Analytics Vidhya.

Data Science 168

Data Science Data mining Analytics Machine Learning 168

Analytics Vidhya

MARCH 3, 2020

Honestly, most data. Data Mining Intermediate Libraries Python Structured Data data exploration feature engineering pandas

Data mining 215

Data mining Structured Data Analytics 215

KDnuggets

DECEMBER 24, 2019

2019 Dec Tutorials, Overviews Apriori Association Rules Data Mining PythonThis article is about Market Basket Analysis & the Apriori algorithm that works behind it.

Marketing 100

Marketing Data mining IT 100

Rocket-Powered Data Science

MAY 20, 2020

In 2019, I was listed as the #1 Top Data Science Blogger to Follow on Twitter. And then there’s this — not a blog, but a link to my 2013 TedX talk: “ Big Data, Small World.” Rocket-Powered Data Science (the website that you are now reading). Big Data Data Science Internet of Things Machine Learning Artificial Intelligence Data Literacy Data MiningI have written articles in many places.

Data Science 169

Data Science Internet of Things Data mining Machine Learning 169

Rocket-Powered Data Science

DECEMBER 16, 2018

In a related post we discussed the Cold Start Problem in Data Science — how do you start to build a model when you have either no training data or no clear choice of model parameters. What data do we have? Which combinations of data have we not explored yet?

Machine Learning 259

Machine Learning Data mining Metrics Modeling 259

Rocket-Powered Data Science

DECEMBER 15, 2018

Specifically, the availability and application of labeled data (things past) for the labeling of previously unseen data (things future) is fundamental to supervised machine learning. Big Data Data Science Machine Learning Products Data Mining

Modeling 191

Modeling Data mining Optimization Metrics 191

Srividya Sridharan

OCTOBER 22, 2019

It’s T minus two weeks to Forrester’s 2nd Data Strategy & Insights Forum in Austin, TX. Over 300 data and analytics leaders will gather to share, learn and get inspired! For those of you who have already registered and planning to attend, you answered one key question during the registration process: What is your top […].

Strategy 56

Strategy Analytics B2B Data mining 56

Decision Management Solutions

FEBRUARY 19, 2020

These different elements will lend themselves to different kinds of technology for automation – some will be rules based, some might use data mining, some might need machine learning algorithms. Focus instead on capturing data about how well the current approach is working and on regular, weekly updates to your decision-making. Automating decisions about transactions lets them be handled in real-time, providing better customer service.

Risk 52

Risk Testing Technology Data mining 52

Rocket-Powered Data Science

APRIL 25, 2019

A few years ago, I generated a list of places to receive data science training. Learn the what, why, and how of Data Science and Machine Learning here. Big Data Data Science Machine Learning Products Training Analytics Data Mining

Data Science 42

Data Science Deep Learning Statistics Data-driven 42

Srividya Sridharan

OCTOBER 16, 2013

Customer insights professionals have many customer analytics methods (sub's reqd) to choose from today to perform behavioral customer analysis, and new techniques emerge as the complexity of customer data increases. Analysis of customer data involves the use of data-mining and statistical methods that span descriptive and predictive analytics. customer analytics customer insights customer intelligence data mining predictive analytics

Statistics 40

Statistics Data mining Predictive Analytics Customer Analytics 40

Decision Management Solutions

DECEMBER 12, 2018

They had some great predictions and suggested priorities around the ethics of analytics, the value of data and the use of AI in fraud and cybersecurity. As they quote in the paper: According to the Rexer Data Science Survey, barely 10 to 15% of companies “almost always” deploy results and another 50% only deploy “often.” This lets business owners get used to analytics and data-driven decisioning and manages technology risk at the same time. Citizen Data Scientists.

Data Science 40

Data Science Publishing Machine Learning Data-driven 40

Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. Honestly, KDD has been promoting data science way before data science was even cool.

KDD 61

KDD Knowledge Discovery Data mining Statistics 61

Ms SQL Girl

JUNE 10, 2015

Chapter 3 Selecting the Data Architecture that Fits Your Organization. Chapter 4 Searching and Combining Data with Power Query. Chapter 6 Discovering and Analyzing Data with Power Pivot. Chapter 9 Discovering Knowledge with Data Mining.

Operational Reporting 52

Operational Reporting Reporting Data Architecture Consulting 52

Ms SQL Girl

JUNE 10, 2015

Chapter 3 Selecting the Data Architecture that Fits Your Organization. Chapter 4 Searching and Combining Data with Power Query. Chapter 6 Discovering and Analyzing Data with Power Pivot. Chapter 9 Discovering Knowledge with Data Mining.

Operational Reporting 52

Operational Reporting Reporting Data Architecture Consulting 52

KDnuggets

DECEMBER 12, 2019

ACM SIGKDD Invites Industry and Academic Experts to Submit Advancements in Data Mining, Knowledge Discovery and Machine Learning for 26 th Annual Conference in San Diego. 2019 Dec Events Applications CA KDD KDD-2020 Research San Diego

KDD 46

KDD Knowledge Discovery Data mining Machine Learning 46

DataFloq

MAY 20, 2020

Raw textual data is often unstructured and is therefore unused by the very businesses that collect it. Until recently, it was nearly impossible to analyze unstructured textual data at scale. Big Data Artificial Intelligence

Technology 266

Technology Predictive Modeling Data mining Machine Learning 266

DataFloq

MAY 27, 2019

They both attempt to make sense of unstructured data, like language, as opposed to structured data like statistics, actions, etc. However, NLP and NLU are opposites of a lot of other data mining techniques.

Data mining 232

Data mining IT Unstructured Data Statistics 232

Data Virtualization

JANUARY 8, 2020

According to CIO magazine, the first chief data officer (CDO) was employed at Capital One in 2002, and since then the role has become widespread, driven by the recent explosion of big data. Business analysis big data Chief Data Officer data assets Data Governance Data Lakes Data Mining data virtualization Data Warehouse; Denodo Platform digital transformation ETL ETL Processes Gartner hadoop Logical Data Warehouse

Data Warehouse 12

Data Warehouse Data mining Digital Transformation Data Lake 12

DataFloq

MAY 19, 2020

Machine learning-based methods of demand forecasting in the retail industry leverage historical data, but the limitations of that data are clear as we grapple with COVID-19. The following are three methods that may boost the accuracy of demand.Short-Term POS Data AnalysisOne proven and efficient technique for identifying shifts in patterns of demand is to analyze the most up-to-date point of sale data. Big Data Artificial Intelligence

Forecasting 180

Forecasting Machine Learning Data mining Sales 180

FineReport

MAY 6, 2020

Setiap hari, kita menjawab pertanyaan tentang skill seorang data analyst. Menurut saya, data analyst nampaknya cuma menganalisis data bisnis dan saya tidak tahu bagaimana cara meningkatkan skill saya.” Ini karena dia tidak sepenuhnya menggali nilai dari analisis big data.

Data mining 83

Data mining Software Data Warehouse Machine Learning 83

DataFloq

SEPTEMBER 9, 2019

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.

Statistics 226

Statistics Machine Learning Unstructured Data Data mining 226

TDAN

MARCH 3, 2020

In 2018, it was discovered that Cambridge Analytica had harvested the data of at least 87 million Facebook users without their knowledge after obtaining it via a few thousand accounts that had used a quiz app. There is no getting away from how incredibly valuable our data is.

Data mining 52

Data mining IT Data Governance Business Intelligence 52

DataFloq

JULY 11, 2019

Data mining. A quick look at any employment-based social networking site is enough to tell that you cloud computing skills are more valuable to employers today than ever before. Some people have gone so far as to say that many companies are in crisis-mode since they can't find people who have the skills they need. Many firms transitioned to cloud-based software deployment models without hiring sufficient numbers of people trained to maintain these kinds of environments.

Data mining 147

Data mining Statistics Software Optimization 147

Smart Data Collective

FEBRUARY 21, 2020

Many careers have been heavily impacted by changes in big data. The big data revolution has had a profound effect on healthcare, marketing and many other fields. One of the fields that has been most affected by big data is electrical engineering.

Big Data 112

Big Data Data mining IoT Testing 112

FineReport

MAY 13, 2020

Although compared to the paid version, not all free BI tool provides stunning data visualization; they offer easy-to-understand charts that can meet your basic needs. Another distinct trait of this software is its feature of data entry. It allows users to ask questions about data.

OLAP 87

OLAP Reporting KPI Data mining 87

FineReport

DECEMBER 10, 2019

Why We Need Data Cleaning?. Data analysis is a time-consuming task, but are you prepared before the data analysis, and have you omitted the important step: data cleaning? For data scientists, we will encounter all kinds of data. Data Quality Guidelines.

Data mining 83

Data mining Data Quality Measurement Statistics 83

Smart Data Collective

JANUARY 29, 2020

However, many federal agencies have finally discovered the countless benefits of big data. The Internal Revenue Service (IRS) is one of the organizations that has started using big data to enforce its policies. Many accounting and bookkeeping services are using big data these days.

Predictive Analytics 64

Predictive Analytics Big Data Data mining Analytics 64

BizAcuity

OCTOBER 21, 2019

Text analytics helps to draw the insights from the unstructured data. . – into structured data to develop actionable managerial insights to enhance their operations. . .

Unstructured Data 80

Unstructured Data Structured Data Data mining Statistics 80

Tamr

AUGUST 14, 2019

Historically, it was nearly impossible for a large enterprise to optimize the use of geospatial data and specifically in relation to other datasets and attributes. The post Geospatial Mapping: The New Frontier of Data Unification appeared first on Tamr Inc.

Data mining 88

Data mining Optimization Machine Learning Visualization 88

BI-Survey

OCTOBER 18, 2018

I t is interesting to see that data integration between on-premises and cloud applications is ranked an equally important use case across all company sizes while data integration between cloud applications becomes more important the smaller the company is.

Data Integration 52

Data Integration Data mining Reporting Modeling 52

Smarten

FEBRUARY 10, 2020

Citizen Data Scientists Will Lead the Charge with Augmented Analytics! You have probably heard a lot about the concept of Citizen Data Scientists in industry conferences and journals.

ROI 68

ROI Data mining Machine Learning Data Science 68

Smart Data Collective

OCTOBER 14, 2019

From the tech industry to retail and finance, big data is encompassing the world as we know it. More organizations rely on big data to help with decision making and to analyze and explore future trends. Big Data Skillsets. billion allocated for data center systems and $90.2

Software 91

Software Big Data Prescriptive Analytics Data mining 91

BizAcuity

MARCH 18, 2019

Predictive Analytics is a toolbox that includes mathematical techniques and processes that are applied to historical data to study correlations, identify trends and predict possible outcomes by quantifying the uncertainty and the characteristics of the variation.

Predictive Analytics 89

Predictive Analytics Uncertainty Data mining Risk 89

Perficient Data & Analytics

OCTOBER 31, 2019

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.

OLAP 56

OLAP Data mining Data Lake Unstructured Data 56

Smart Data Collective

APRIL 8, 2020

sThe recent years have seen a tremendous surge in data generation levels , characterized by the dramatic digital transformation occurring in myriad enterprises across the industrial landscape. The amount of data being generated globally is increasing at rapid rates.

Technology 105

Technology Data Warehouse Machine Learning Business Intelligence 105

Smart Data Collective

JUNE 11, 2019

Big data is everywhere , and it’s finding its way into a multitude of industries and applications. One of the most fascinating big data industries is manufacturing. In an environment of fast-paced production and competitive markets, big data helps companies rise to the top and stay efficient and relevant. Manufacturing innovation has long been an integral piece of our economic success, and it seems that big data allows for great industry gains.

Manufacturing 85

Manufacturing Data mining Analytics Forecasting 85