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12/12/2022

Building a highperformance data and AI organization

Organizations’ top data priorities over the next two years fall into three areas, all supported by wider adoption of cloud platforms: improving data management, enhancing data analytics and ML, and expanding the use of all types of enterprise data, including streaming and unstructured data.

• Technology-enabled collaboration is creating a working data culture. The CDOs interviewed for the study ascribe great importance to democratizing analytics and ML capabilities. Pushing these to the edge with advanced data technologies will help end-users to make more informed business decisions — the hallmarks of a strong data culture. This is only possible with a modern data architecture. One CDO sums it up by saying that successful data management is achieved when the right users have access to the right data to quickly generate insights that drive business value.

https://etechintel.com/building-a-high-performance-data-and-ai-organization/

09/12/2022

Building the Data Lakehouse

Most evolutions occur over eons of time. The evolution occurs so slowly that the steps in the evolution are not observable on a day-to-day basis. Watching the daily progression of an evolution makes watching paint dry look like a spectator sport. However, the evolution of computer technology has progressed at warp speed, starting in the 1960s.

𝗧𝗵𝗲 𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆

Once upon a time, life was simple when it came to the computer. Data went in, was processed, and data came out. In the beginning, there was paper tape. Paper tape was automated but stored a minuscule amount of data in a fixed format. Then came punched cards. One of the problems with punched cards was that they were in a fixed format. Huge volumes of punched cards consumed huge amounts of paper and dropping a deck of cards led to a tedious effort to get the cards back in order.

https://etechintel.com/building-the-data-lakehouse/

07/12/2022

The Big Book of Data Engineering

Organizations realize the value data plays as a strategic asset for various business-related initiatives, such as growing revenues, improving the customer experience, operating efficiently or improving a product or service. However, accessing and managing data for these initiatives has become increasingly complex. Most of the complexity has arisen with the explosion of data volumes and data types, with organizations amassing an estimated 80% of data in unstructured and semi-structured format. As the collection of data continues to increase, 73% of the data goes unused for analytics or decision-making. In order to try and decrease this percentage and make more data usable, data engineering teams are responsible for building data pipelines to efficiently and reliably deliver data. But the process of building these complex data pipelines comes with a number of difficulties:

https://etechintel.com/the-big-book-of-data-engineering/

05/12/2022

Data Management 101 on Databricks

Ultimately, the consistent and reliable flow of data across people, teams and business functions is crucial to an organization’s survival and ability to innovate. And while we are seeing companies realize the value of their data — through data-driven product decisions, more collaboration or rapid movement into new channels — most businesses struggle to manage and leverage data correctly.

The vast majority of company data today flows into a data lake, where teams do data prep and validation in order to serve downstream data science and machine learning initiatives. At the same time, a huge amount of data is transformed and sent to many different downstream data warehouses for business intelligence (BI), because traditional data lakes are too slow and unreliable for BI workloads. Depending on the workload, data sometimes also needs to be moved out of the data warehouse back to the data lake. And increasingly, machine learning workloads are also reading and writing to data warehouses. The underlying reason why this kind of data management is challenging is that there are inherent differences between data lakes and data warehouses.

https://etechintel.com/data-management-101-on-databricks/

25/11/2022

Streamlining the Marketing-to-Sales Pipeline

There’s an art to growing leads and maintaining successful relationships with customers. When you want to give your sales and marketing teams a digital advantage, you need solutions that augment those soft people-skills with science. For a new generation of business leaders, this means making data central to the decision making process. It’s about anticipating customer needs before they arise. The stakes are high for companies as customers expect optimal convenience, availability, and flexibility. It’s more vital than ever to synchronize transactional, observational, and behavioral data to drive the customer experience.

Powerful new sales and marketing tools are available to level-up your business strategy. AIdriven solutions can surface insights and provide proactive guidance to field teams. Marketing and sales no longer have to exist in separate silos— they can integrate so that the left hand truly understands what the right hand is doing. The days of relying on guesswork and legacy CRM solutions to drive the customer experience are fading into the past. Now’s the time to empower your teams with data, giving them the freedom to do what they do best—cultivate relationships and close deals.

https://etechintel.com/streamlining-the-marketing-to-sales-pipeline/

23/11/2022

Mitsubishi Heavy Industries Constructs Digital Transformation with Looker

It is no exaggeration to say that Mitsubishi Heavy Industries, Ltd is a company that built the history of Japan’s manufacturing industry. The company is constructed of three main business domains: the “Power” division that manufactures nuclear and thermal power generators, the “Aviation/Defense/Space” division that manufactures aircrafts and rockets, and the “Industry & Social Infrastructure” division that manufactures machinery from shipbuilding to chemical plants and beyond. The group’s consolidated net sales exceed 4 trillion yen ($37 billion USD).

The rapid global digitalization era that organizations are navigating today poses huge challenges for a heavyweight manufacturing business. The Digitalization Promotion Group at Mitsubishi Heavy Industries has taken on the task of designing how the company can overcome these challenges through digital transformation. Until March 2020, this group was under the management of the Business Strategy Team within the domains of Industry & Social Infrastructure.

https://etechintel.com/mitsubishi-heavy-industries-constructs-digital-transformation-with-looker/

21/11/2022

CHOOSING THE RIGHT STRUCTURE FOR YOUR REWARDS PROGRAM

Rewards and incentives are a great way to boost your market research insights and response rates. But should you use instant rewards, sweepstakes, or points-to-rewards?

Use our cheat sheet to determine which type of rewards program is best to achieve your goals, whatever they may be — increasing survey responses, encouraging focus group participation, or keeping panel and community members engaged. It compares instant rewards, sweepstakes, and points by exploring:

What results they can bring
How they fit into your budget
The unique advantages of each
Any challenges they create
Their best use cases

https://etechintel.com/choosing-the-right-structure-for-your-rewards-program/

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